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ORCIDPeter Stone 0001
Person information
- affiliation: University of Texas at Austin, TX, USA
- affiliation: Sony AI, Tokyo, Japan
- affiliation (1999 - 2002): AT&T Labs, Florham Park, NJ, USA
- affiliation (PhD 1998): Carnegie Mellon University, Pittsburgh, PA, USA
Other persons with the same name
- Peter Stone 0002 — University of Sussex Library, Brighton, UK
- Peter Stone 0003 — University of Essex, UK
- Peter Stone 0004 — University of Auckland, Department of Obstetrics and Gynaecology, New Zealand
- Peter Stone 0005 — CSIRO Land and Water, Brisbane, QLD, Australia
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2020 – today
- 2025
[j126]Rohan Chandra, Vrushabh Zinage, Efstathios Bakolas, Peter Stone, Joydeep Biswas:
Deadlock-free, safe, and decentralized multi-robot navigation in social mini-games via discrete-time control barrier functions. Auton. Robots 49(2): 12 (2025)- [j125]Peter Stone
:
Artificial Intelligence: Looking Forward 15 Years. IEEE Intell. Syst. 40(1): 25-29 (2025) - [j124]Peter Stone, Matthew Ebert, Wenchao Zhou, Ergun Akleman, Vinayak R. Krishnamurthy, Zhenghui Sha:
SafeZone*: A Graph-Based and Time-Optimal Cooperative 3D Printing Framework. J. Comput. Inf. Sci. Eng. 25(4) (2025) - [j123]Luisa Mao, Garrett Warnell, Peter Stone, Joydeep Biswas:
pacer: Preference-Conditioned All-Terrain Costmap Generation. IEEE Robotics Autom. Lett. 10(5): 4572-4579 (2025) - [j122]Anthony G. Francis, Claudia Pérez-D'Arpino, Chengshu Li, Fei Xia, Alexandre Alahi, Rachid Alami, Aniket Bera, Abhijat Biswas, Joydeep Biswas, Rohan Chandra, Hao-Tien Lewis Chiang, Michael Everett, Sehoon Ha, Justin W. Hart, Jonathan P. How, Haresh Karnan, Tsang-Wei Edward Lee, Luis J. Manso, Reuth Mirsky, Sören Pirk, Phani-Teja Singamaneni, Peter Stone, Ada V. Taylor, Peter Trautman, Nathan Tsoi, Marynel Vázquez, Xuesu Xiao, Peng Xu, Naoki Yokoyama, Alexander Toshev, Roberto Martín-Martín:
Principles and Guidelines for Evaluating Social Robot Navigation Algorithms. ACM Trans. Hum. Robot Interact. 14(2): 34:1-34:65 (2025) - [c483]Chen Tang, Ben Abbatematteo, Jiaheng Hu, Rohan Chandra, Roberto Martín-Martín, Peter Stone:
Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes. AAAI 2025: 28698-28699 - [c482]Joydeep Biswas, Don Fussell, Peter Stone, Kristin Patterson, Kristen Procko, Lea Sabatini, Zifan Xu:
The Essentials of AI for Life and Society: An AI Literacy Course for the University Community. AAAI 2025: 28973-28978 - [c481]Alexander Levine, Peter Stone, Amy Zhang:
Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory. ICLR 2025 - [c480]Bo Liu, Rui Wang, Lemeng Wu, Yihao Feng, Peter Stone, Qiang Liu:
Longhorn: State Space Models are Amortized Online Learners. ICLR 2025 - [c479]Hojoon Lee, Dongyoon Hwang, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter R. Wurman, Jaegul Choo, Peter Stone, Takuma Seno:
SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning. ICLR 2025 - [i179]Stephane Hatgis-Kessell, W. Bradley Knox, Serena Booth, Scott Niekum, Peter Stone:
Influencing Humans to Conform to Preference Models for RLHF. CoRR abs/2501.06416 (2025) - [i178]Joydeep Biswas, Don Fussell, Peter Stone, Kristin Patterson, Kristen Procko, Lea Sabatini, Zifan Xu:
The Essentials of AI for Life and Society: An AI Literacy Course for the University Community. CoRR abs/2501.07392 (2025) - [i177]Hojoon Lee, Youngdo Lee, Takuma Seno, Donghu Kim, Peter Stone, Jaegul Choo:
Hyperspherical Normalization for Scalable Deep Reinforcement Learning. CoRR abs/2502.15280 (2025) - [i176]Alexander Levine, Peter Stone, Amy Zhang:
Offline Action-Free Learning of Ex-BMDPs by Comparing Diverse Datasets. CoRR abs/2503.21018 (2025) - 2024
- [j121]Alexander Levine, Peter Stone, Amy Zhang:
Multistep Inverse Is Not All You Need. RLJ 2: 884-925 (2024) - [j120]Miguel Vasco, Takuma Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, Peter Stone:
A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo. RLJ 4: 1674-1710 (2024) - [j119]Alessandra Rossi, Maike Paetzel-Prüsmann, Merel Keijsers, Michael Anderson, Susan Leigh Anderson, Daniel Barry, Jan Gutsche, Justin W. Hart, Luca Iocchi, Ainse Kokkelmans, Wouter Kuijpers, Yun Liu, Daniel Polani, Caleb Rascón, Marcus Scheunemann, Peter Stone, Florian Vahl, René van de Molengraft, Oskar von Stryk:
The human in the loop Perspectives and challenges for RoboCup 2050. Auton. Robots 48(2-3): 8 (2024) - [j118]Eric Horvitz, Vincent Conitzer, Sheila A. McIlraith, Peter Stone:
Now, Later, and Lasting: 10 Priorities for AI Research, Policy, and Practice. Commun. ACM 67(6): 39-40 (2024) - [j117]Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman, Eric Eaton, Benjamin Epstein, Yunhao Ge, Lucy Halperin, Jonathan P. How, Laurent Itti, Michael A. Jacobs, Pavan Kantharaju, Long Le, Steven Lee, Xinran Liu, Sildomar T. Monteiro, David Musliner, Saptarshi Nath, Priyadarshini Panda, Christos Peridis, Hamed Pirsiavash, Vishwa S. Parekh, Kaushik Roy, Shahaf S. Shperberg, Hava T. Siegelmann, Peter Stone, Kyle Vedder, Jingfeng Wu, Lin Yang, Guangyao Zheng, Soheil Kolouri:
A collective AI via lifelong learning and sharing at the edge. Nat. Mac. Intell. 6(3): 251-264 (2024) - [j116]Xuesu Xiao, Zifan Xu, Aniket Datar, Garrett Warnell, Peter Stone, Joshua Julian Damanik, Jaewon Jung, Chala Adane Deresa, Than Duc Huy, Chen Jinyu, Chen Yichen, Joshua Adrian Cahyono, Jingda Wu, Longfei Mo, Mingyang Lv, Bowen Lan, Qingyang Meng, Weizhi Tao, Li Cheng:
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned From the Third BARN Challenge at ICRA 2024 [Competitions]. IEEE Robotics Autom. Mag. 31(3): 197-204 (2024) - [j115]Shiqi Zhang, Piyush Khandelwal, Peter Stone:
iCORPP: Interleaved commonsense reasoning and probabilistic planning on robots. Robotics Auton. Syst. 174: 104613 (2024) - [j114]Reuth Mirsky, Xuesu Xiao, Justin W. Hart, Peter Stone:
Conflict Avoidance in Social Navigation - a Survey. ACM Trans. Hum. Robot Interact. 13(1): 13:1-13:36 (2024) - [j113]W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Gabriele Allievi:
Models of human preference for learning reward functions. Trans. Mach. Learn. Res. 2024 (2024) - [c478]W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum:
Learning Optimal Advantage from Preferences and Mistaking It for Reward. AAAI 2024: 10066-10073 - [c477]Zizhao Wang, Caroline Wang, Xuesu Xiao, Yuke Zhu, Peter Stone:
Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning. AAAI 2024: 15778-15786 - [c476]Muhammad Rahman, Jiaxun Cui, Peter Stone:
Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents. AAAI 2024: 17523-17530 - [c475]W. Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone:
Reward (Mis)design for Autonomous Driving (Abstract Reprint). AAAI 2024: 22702 - [c474]Catherine Weaver, Roberto Capobianco, Peter R. Wurman, Peter Stone, Masayoshi Tomizuka:
Real-Time Trajectory Generation via Dynamic Movement Primitives for Autonomous Racing. ACC 2024: 352-359 - [c473]Shahaf S. Shperberg, Bo Liu, Peter Stone:
Relaxed Exploration Constrained Reinforcement Learning. AAMAS 2024: 1727-1735 - [c472]William Yue, Bo Liu, Peter Stone:
Overview of t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making. AAMAS 2024: 2579-2581 - [c471]William Yue, Bo Liu, Peter Stone:
t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making. CoLLAs 2024: 481-497 - [c470]Shivin Dass, Jiaheng Hu, Ben Abbatematteo, Peter Stone, Roberto Martín-Martín:
Learning to Look: Seeking Information for Decision Making via Policy Factorization. CoRL 2024: 4425-4445 - [c469]Zifan Xu, Haozhu Wang, Dmitriy Bespalov, Xian Wu, Peter Stone, Yanjun Qi:
LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning. EMNLP (Findings) 2024: 3624-3643 - [c468]Ziping Xu, Zifan Xu, Runxuan Jiang, Peter Stone, Ambuj Tewari:
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks. ICLR 2024 - [c467]Zifan Xu, Amir Hossain Raj, Xuesu Xiao, Peter Stone:
Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning. ICRA 2024: 11474-11480 - [c466]Haresh Karnan, Elvin Yang, Garrett Warnell, Joydeep Biswas, Peter Stone:
Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning. ICRA 2024: 13008-13014 - [c465]Amir Hossain Raj, Zichao Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter Stone, Joydeep Biswas, Xuesu Xiao:
Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds. ICRA 2024: 16330-16337 - [c464]Yoonchang Sung, Rahul Shome, Peter Stone:
Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning. ICRA 2024: 17086-17092 - [c463]Jiaheng Hu, Zizhao Wang, Peter Stone, Roberto Martín-Martín:
Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning. NeurIPS 2024 - [c462]Borja G. León, Francesco Riccio, Kaushik Subramanian, Peter R. Wurman, Peter Stone:
Discovering Creative Behaviors through DUPLEX: Diverse Universal Features for Policy Exploration. NeurIPS 2024 - [c461]Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone:
SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions. NeurIPS 2024 - [c460]Caroline Wang, Arrasy Rahman, Ishan Durugkar, Elad Liebman, Peter Stone:
N-agent Ad Hoc Teamwork. NeurIPS 2024 - [c459]Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi, Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, Justin W. Hart:
Dobby: A Conversational Service Robot Driven by GPT-4. RO-MAN 2024: 1362-1369 - [i175]William Yue, Bo Liu, Peter Stone:
t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making. CoRR abs/2401.02576 (2024) - [i174]Zizhao Wang, Caroline Wang, Xuesu Xiao, Yuke Zhu, Peter Stone:
Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning. CoRR abs/2401.12497 (2024) - [i173]Ziping Xu, Zifan Xu, Runxuan Jiang, Peter Stone, Ambuj Tewari:
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks. CoRR abs/2403.01636 (2024) - [i172]Zifan Xu, Amir Hossain Raj, Xuesu Xiao, Peter Stone:
Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning. CoRR abs/2403.03848 (2024) - [i171]Shivin Dass, Wensi Ai, Yuqian Jiang, Samik Singh, Jiaheng Hu, Ruohan Zhang, Peter Stone, Ben Abbatematteo, Roberto Martín-Martín:
TeleMoMa: A Modular and Versatile Teleoperation System for Mobile Manipulation. CoRR abs/2403.07869 (2024) - [i170]Alexander Levine, Peter Stone, Amy Zhang:
Multistep Inverse Is Not All You Need. CoRR abs/2403.11940 (2024) - [i169]Saad Abdul Ghani, Zizhao Wang, Peter Stone, Xuesu Xiao:
Dyna-LfLH: Learning Agile Navigation in Dynamic Environments from Learned Hallucination. CoRR abs/2403.17231 (2024) - [i168]Eric Horvitz, Vincent Conitzer, Sheila A. McIlraith, Peter Stone:
Now, Later, and Lasting: Ten Priorities for AI Research, Policy, and Practice. CoRR abs/2404.04750 (2024) - [i167]Caroline Wang, Arrasy Rahman, Ishan Durugkar, Elad Liebman, Peter Stone:
N-Agent Ad Hoc Teamwork. CoRR abs/2404.10740 (2024) - [i166]Rolando Fernandez, Garrett Warnell, Derrik E. Asher, Peter Stone:
Multi-Agent Synchronization Tasks. CoRR abs/2404.18798 (2024) - [i165]Caleb Chuck, Carl Qi, Michael J. Munje, Shuozhe Li, Max Rudolph, Chang Shi, Siddhant Agarwal, Harshit Sikchi, Abhinav Peri, Sarthak Dayal, Evan Kuo, Kavan Mehta, Anthony Wang, Peter Stone, Amy Zhang, Scott Niekum:
Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning. CoRR abs/2405.03113 (2024) - [i164]Rohan Chandra, Haresh Karnan, Negar Mehr, Peter Stone, Joydeep Biswas:
Towards Imitation Learning in Real World Unstructured Social Mini-Games in Pedestrian Crowds. CoRR abs/2405.16439 (2024) - [i163]Yifeng Zhu, Arisrei Lim, Peter Stone, Yuke Zhu:
Vision-based Manipulation from Single Human Video with Open-World Object Graphs. CoRR abs/2405.20321 (2024) - [i162]Miguel Vasco, Takuma Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, Peter Stone:
A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo. CoRR abs/2406.12563 (2024) - [i161]Yuxin Chen, Chen Tang, Chenran Li, Ran Tian, Peter Stone, Masayoshi Tomizuka, Wei Zhan:
MEReQ: Max-Ent Residual-Q Inverse RL for Sample-Efficient Alignment from Intervention. CoRR abs/2406.16258 (2024) - [i160]Xuesu Xiao, Zifan Xu, Aniket Datar, Garrett Warnell, Peter Stone, Joshua Julian Damanik, Jaewon Jung, Chala Adane Deresa, Than Duc Huy, Chen Jinyu, Chen Yichen, Joshua Adrian Cahyono, Jingda Wu, Longfei Mo, Mingyang Lv, Bowen Lan, Qingyang Meng, Weizhi Tao, Li Cheng:
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The 3rd BARN Challenge at ICRA 2024. CoRR abs/2407.01862 (2024) - [i159]Bo Liu, Rui Wang, Lemeng Wu, Yihao Feng, Peter Stone, Qiang Liu:
Longhorn: State Space Models are Amortized Online Learners. CoRR abs/2407.14207 (2024) - [i158]Chen Tang, Ben Abbatematteo, Jiaheng Hu, Rohan Chandra, Roberto Martín-Martín, Peter Stone:
Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes. CoRR abs/2408.03539 (2024) - [i157]Mingyo Seo, Yoonyoung Cho, Yoonchang Sung, Peter Stone, Yuke Zhu, Beomjoon Kim:
PRESTO: Fast motion planning using diffusion models based on key-configuration environment representation. CoRR abs/2409.16012 (2024) - [i156]Jiaheng Hu, Rose Hendrix, Ali Farhadi, Aniruddha Kembhavi, Roberto Martin Martin, Peter Stone, Kuo-Hao Zeng, Kiana Ehsani:
FLaRe: Achieving Masterful and Adaptive Robot Policies with Large-Scale Reinforcement Learning Fine-Tuning. CoRR abs/2409.16578 (2024) - [i155]Linji Wang, Zifan Xu, Peter Stone, Xuesu Xiao:
Grounded Curriculum Learning. CoRR abs/2409.19816 (2024) - [i154]Bo Liu, Mao Ye, Peter Stone, Qiang Liu:
Fine-Grained Gradient Restriction: A Simple Approach for Mitigating Catastrophic Forgetting. CoRR abs/2410.00868 (2024) - [i153]Alexander Levine, Peter Stone, Amy Zhang:
Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory. CoRR abs/2410.03016 (2024) - [i152]Yoonchang Sung, Shahaf S. Shperberg, Qi Wang, Peter Stone:
Effort Allocation for Deadline-Aware Task and Motion Planning: A Metareasoning Approach. CoRR abs/2410.05828 (2024) - [i151]Hojoon Lee, Dongyoon Hwang, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter R. Wurman, Jaegul Choo, Peter Stone, Takuma Seno:
SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning. CoRR abs/2410.09754 (2024) - [i150]Jiaheng Hu, Zizhao Wang, Peter Stone, Roberto Martín-Martín:
Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning. CoRR abs/2410.11251 (2024) - [i149]Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone:
SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions. CoRR abs/2410.18416 (2024) - [i148]Shivin Dass, Jiaheng Hu, Ben Abbatematteo, Peter Stone, Roberto Martín-Martín:
Learning to Look: Seeking Information for Decision Making via Policy Factorization. CoRR abs/2410.18964 (2024) - [i147]Luisa Mao, Garrett Warnell, Peter Stone, Joydeep Biswas:
PACER: Preference-conditioned All-terrain Costmap Generation. CoRR abs/2410.23488 (2024) - [i146]William Yue, Bo Liu, Peter Stone:
Learning Memory Mechanisms for Decision Making through Demonstrations. CoRR abs/2411.07954 (2024) - [i145]Siddhant Agarwal, Harshit Sikchi, Peter Stone, Amy Zhang:
Proto Successor Measure: Representing the Space of All Possible Solutions of Reinforcement Learning. CoRR abs/2411.19418 (2024) - [i144]Harshit Sikchi, Siddhant Agarwal, Pranaya Jajoo, Samyak Parajuli, Caleb Chuck, Max Rudolph, Peter Stone, Amy Zhang, Scott Niekum:
RL Zero: Zero-Shot Language to Behaviors without any Supervision. CoRR abs/2412.05718 (2024) - [i143]Adam Labiosa, Zhihan Wang, Siddhant Agarwal, William Cong, Geethika Hemkumar, Abhinav Narayan Harish, Benjamin Hong, Josh Kelle, Chen Li, Yuhao Li, Zisen Shao, Peter Stone, Josiah P. Hanna:
Reinforcement Learning Within the Classical Robotics Stack: A Case Study in Robot Soccer. CoRR abs/2412.09417 (2024) - 2023
- [j112]W. Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone:
Reward (Mis)design for autonomous driving. Artif. Intell. 316: 103829 (2023) - [j111]Xiaohan Zhang, Saeid Amiri, Jivko Sinapov, Jesse Thomason, Peter Stone, Shiqi Zhang:
Multimodal embodied attribute learning by robots for object-centric action policies. Auton. Robots 47(5): 505-528 (2023) - [j110]Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha:
A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks 160: 274-296 (2023) - [j109]Xuesu Xiao, Zifan Xu, Garrett Warnell, Peter Stone, Ferran Gebelli Guinjoan, Rômulo T. Rodrigues, Herman Bruyninckx, Hanjaya Mandala, Guilherme Christmann, José Luis Blanco-Claraco, Shravan Somashekara Rai:
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned From the Second BARN Challenge at ICRA 2023 [Competitions]. IEEE Robotics Autom. Mag. 30(4): 91-97 (2023) - [j108]Varun Raj Kompella, Thomas Walsh, Samuel Barrett, Peter R. Wurman, Peter Stone:
Event Tables for Efficient Experience Replay. Trans. Mach. Learn. Res. 2023 (2023) - [c458]Serena Booth, W. Bradley Knox, Julie Shah, Scott Niekum, Peter Stone, Alessandro Allievi:
The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications. AAAI 2023: 5920-5929 - [c457]Bo Liu, Yihao Feng, Qiang Liu, Peter Stone:
Metric Residual Network for Sample Efficient Goal-Conditioned Reinforcement Learning. AAAI 2023: 8799-8806 - [c456]Caroline Wang, Ishan Durugkar, Elad Liebman, Peter Stone:
DM²: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching. AAAI 2023: 11699-11707 - [c455]Vaibhav Bajaj, Guni Sharon, Peter Stone:
Task Phasing: Automated Curriculum Learning from Demonstrations. ICAPS 2023: 542-550 - [c454]Caroline Wang, Garrett Warnell, Peter Stone:
D-Shape: Demonstration-Shaped Reinforcement Learning via Goal-Conditioning. AAMAS 2023: 1267-1275 - [c453]Shahaf S. Shperberg, Bo Liu, Peter Stone:
Relaxed Exploration Constrained Reinforcement Learning. AAMAS 2023: 2821-2823 - [c452]Zifan Xu, Yulin Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian Jiang, Bo Liu, Peter Stone:
Model-Based Meta Automatic Curriculum Learning. CoLLAs 2023: 846-860 - [c451]Haresh Karnan, Elvin Yang, Daniel Farkash, Garrett Warnell, Joydeep Biswas, Peter Stone:
STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience. CoRL 2023: 2393-2413 - [c450]Yifeng Zhu, Zhenyu Jiang, Peter Stone, Yuke Zhu:
Learning Generalizable Manipulation Policies with Object-Centric 3D Representations. CoRL 2023: 3418-3433 - [c449]Swathi Mannem, William Macke, Peter Stone, Reuth Mirsky:
Exploring the Cost of Interruptions in Human-Robot Teaming. Humanoids 2023: 1-8 - [c448]Jiaxun Cui, Xiaomeng Yang, Mulong Luo, Geunbae Lee, Peter Stone, Hsien-Hsin S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, Yuandong Tian:
MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection. ICLR 2023 - [c447]Zifan Xu, Bo Liu, Xuesu Xiao, Anirudh Nair, Peter Stone:
Benchmarking Reinforcement Learning Techniques for Autonomous Navigation. ICRA 2023: 9224-9230 - [c446]Jin Soo Park, Xuesu Xiao, Garrett Warnell, Harel Yedidsion, Peter Stone:
Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways. ICRA 2023: 10033-10039 - [c445]Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu, Peter Stone, Shiqi Zhang:
Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning. IROS 2023: 866-872 - [c444]Keya Ghonasgi, Reuth Mirsky, Adrian M. Haith, Peter Stone, Ashish D. Deshpande:
A Novel Control Law for Multi-Joint Human-Robot Interaction Tasks While Maintaining Postural Coordination. IROS 2023: 6110-6116 - [c443]Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang:
f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences. NeurIPS 2023 - [c442]Bo Liu, Yihao Feng, Peter Stone, Qiang Liu:
FAMO: Fast Adaptive Multitask Optimization. NeurIPS 2023 - [c441]Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, Peter Stone:
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning. NeurIPS 2023 - [c440]Zizhao Wang, Jiaheng Hu, Peter Stone, Roberto Martín-Martín:
ELDEN: Exploration via Local Dependencies. NeurIPS 2023 - [c439]Jiaheng Hu, Peter Stone, Roberto Martín-Martín:
Causal Policy Gradient for Whole-Body Mobile Manipulation. Robotics: Science and Systems 2023 - [c438]Yoonchang Sung, Peter Stone:
Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search. Robotics: Science and Systems 2023 - [c437]Elliott Hauser, Yao-Cheng Chan, Parth Chonkar, Geethika Hemkumar, Huihai Wang, Daksh Dua, Shikhar Gupta, Efren Mendoza Enriquez, Tiffany Kao, Justin W. Hart, Reuth Mirsky, Joydeep Biswas, Junfeng Jiao, Peter Stone:
"What's That Robot Doing Here?": Perceptions Of Incidental Encounters With Autonomous Quadruped Robots. TAS 2023: 12:1-12:15 - [c436]Dustin Morrill, Thomas J. Walsh, Daniel Hernandez, Peter R. Wurman, Peter Stone:
Composing Efficient, Robust Tests for Policy Selection. UAI 2023: 1456-1466 - [i142]Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Dimitri Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha:
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems. CoRR abs/2301.07799 (2023) - [i141]Bo Liu, Yuqian Jiang, Xiaohan Zhang, Qiang Liu, Shiqi Zhang, Joydeep Biswas, Peter Stone:
LLM+P: Empowering Large Language Models with Optimal Planning Proficiency. CoRR abs/2304.11477 (2023) - [i140]Jiaheng Hu, Peter Stone, Roberto Martín-Martín:
Causal Policy Gradient for Whole-Body Mobile Manipulation. CoRR abs/2305.04866 (2023) - [i139]Yoonchang Sung, Peter Stone:
Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search. CoRR abs/2305.10395 (2023) - [i138]Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, Peter Stone:
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning. CoRR abs/2306.03310 (2023) - [i137]Bo Liu, Yihao Feng, Peter Stone, Qiang Liu:
FAMO: Fast Adaptive Multitask Optimization. CoRR abs/2306.03792 (2023) - [i136]Dustin Morrill, Thomas J. Walsh, Daniel Hernandez, Peter R. Wurman, Peter Stone:
Composing Efficient, Robust Tests for Policy Selection. CoRR abs/2306.07372 (2023) - [i135]Anthony G. Francis, Claudia Pérez-D'Arpino, Chengshu Li, Fei Xia, Alexandre Alahi, Rachid Alami, Aniket Bera, Abhijat Biswas, Joydeep Biswas, Rohan Chandra, Hao-Tien Lewis Chiang, Michael Everett, Sehoon Ha, Justin W. Hart, Jonathan P. How, Haresh Karnan, Tsang-Wei Edward Lee, Luis J. Manso, Reuth Mirsky, Sören Pirk, Phani-Teja Singamaneni, Peter Stone, Ada V. Taylor, Peter Trautman, Nathan Tsoi, Marynel Vázquez, Xuesu Xiao, Peng Xu, Naoki Yokoyama, Alexander Toshev, Roberto Martin Martin:
Principles and Guidelines for Evaluating Social Robot Navigation Algorithms. CoRR abs/2306.16740 (2023) - [i134]Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu, Peter Stone, Shiqi Zhang:
Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning. CoRR abs/2307.11889 (2023) - [i133]Xuesu Xiao, Zifan Xu, Garrett Warnell, Peter Stone, Ferran Gebelli Guinjoan, Rômulo T. Rodrigues, Herman Bruyninckx, Hanjaya Mandala, Guilherme Christmann, José Luis Blanco-Claraco, Shravan Somashekara Rai:
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The 2nd BARN Challenge at ICRA 2023. CoRR abs/2308.03205 (2023) - [i132]Arrasy Rahman, Jiaxun Cui, Peter Stone:
Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents. CoRR abs/2308.09595 (2023) - [i131]Rohan Chandra, Vrushabh Zinage, Efstathios Bakolas, Joydeep Biswas, Peter Stone:
Decentralized Multi-Robot Social Navigation in Constrained Environments via Game-Theoretic Control Barrier Functions. CoRR abs/2308.10966 (2023) - [i130]Elad Liebman, Peter Stone:
Utilizing Mood-Inducing Background Music in Human-Robot Interaction. CoRR abs/2308.14269 (2023) - [i129]Yoonchang Sung, Rahul Shome, Peter Stone:
Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning. CoRR abs/2309.08897 (2023) - [i128]Haresh Karnan, Elvin Yang, Garrett Warnell, Joydeep Biswas, Peter Stone:
Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference Aligned Path Planning. CoRR abs/2309.09912 (2023) - [i127]Amir Hossain Raj, Zichao Hu, Haresh Karnan, Rohan Chandra, Amirreza Payandeh, Luisa Mao, Peter Stone, Joydeep Biswas, Xuesu Xiao:
Targeted Learning: A Hybrid Approach to Social Robot Navigation. CoRR abs/2309.13466 (2023) - [i126]Haresh Karnan, Elvin Yang, Daniel Farkash, Garrett Warnell, Joydeep Biswas, Peter Stone:
Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience. CoRR abs/2309.15302 (2023) - [i125]W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum:
Learning Optimal Advantage from Preferences and Mistaking it for Reward. CoRR abs/2310.02456 (2023) - [i124]Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi, Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, Justin W. Hart:
Dobby: A Conversational Service Robot Driven by GPT-4. CoRR abs/2310.06303 (2023) - [i123]Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang:
f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences. CoRR abs/2310.06794 (2023) - [i122]Jiaheng Hu, Zizhao Wang, Peter Stone, Roberto Martin Martin:
ELDEN: Exploration via Local Dependencies. CoRR abs/2310.08702 (2023) - [i121]Yifeng Zhu, Zhenyu Jiang, Peter Stone, Yuke Zhu:
Learning Generalizable Manipulation Policies with Object-Centric 3D Representations. CoRR abs/2310.14386 (2023) - [i120]Swathi Mannem, William Macke, Peter Stone, Reuth Mirsky:
Exploring the Cost of Interruptions in Human-Robot Teaming. CoRR abs/2311.00785 (2023) - [i119]Sveta Paster, Kantwon Rogers, Gordon Briggs, Peter Stone, Reuth Mirsky:
ICRA Roboethics Challenge 2023: Intelligent Disobedience in an Elderly Care Home. CoRR abs/2311.08783 (2023) - [i118]Zifan Xu, Haozhu Wang, Dmitriy Bespalov, Peter Stone, Yanjun Qi:
Latent Skill Discovery for Chain-of-Thought Reasoning. CoRR abs/2312.04684 (2023) - 2022
- [j107]Xuesu Xiao, Bo Liu, Garrett Warnell, Peter Stone:
Motion planning and control for mobile robot navigation using machine learning: a survey. Auton. Robots 46(5): 569-597 (2022) - [j106]Peter R. Wurman, Peter Stone, Michael Spranger:
Challenges and Opportunities of Applying Reinforcement Learning to Autonomous Racing. IEEE Intell. Syst. 37(3): 20-23 (2022) - [j105]Michael Albert, Vincent Conitzer, Giuseppe Lopomo, Peter Stone:
Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization. Oper. Res. 70(1): 562-584 (2022) - [j104]Peter R. Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas J. Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Piyush Khandelwal, Varun Raj Kompella, HaoChih Lin, Patrick MacAlpine, Declan Oller, Takuma Seno, Craig Sherstan, Michael D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead, Peter Dürr, Peter Stone, Michael Spranger, Hiroaki Kitano:
Outracing champion Gran Turismo drivers with deep reinforcement learning. Nat. 602(7896): 223-228 (2022) - [j103]Yunshu Du, Garrett Warnell, Assefaw H. Gebremedhin, Peter Stone, Matthew E. Taylor:
Lucid dreaming for experience replay: refreshing past states with the current policy. Neural Comput. Appl. 34(3): 1687-1712 (2022) - [j102]Yifeng Zhu, Peter Stone, Yuke Zhu:
Bottom-Up Skill Discovery From Unsegmented Demonstrations for Long-Horizon Robot Manipulation. IEEE Robotics Autom. Lett. 7(2): 4126-4133 (2022) - [j101]Haresh Karnan, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Sören Pirk, Alexander Toshev, Justin W. Hart, Joydeep Biswas, Peter Stone:
Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset of Demonstrations for Social Navigation. IEEE Robotics Autom. Lett. 7(4): 11807-11814 (2022) - [j100]Xuesu Xiao, Zifan Xu, Zizhao Wang, Yunlong Song, Garrett Warnell, Peter Stone, Tingnan Zhang, Shravan Ravi, Gary Wang, Haresh Karnan, Joydeep Biswas, Nicholas Mohammad, Lauren Bramblett, Rahul Peddi, Nicola Bezzo, Zhanteng Xie, Philip M. Dames:
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned From the Benchmark Autonomous Robot Navigation Challenge at ICRA 2022 [Competitions]. IEEE Robotics Autom. Mag. 29(4): 148-156 (2022) - [j99]Xuesu Xiao, Zizhao Wang, Zifan Xu, Bo Liu, Garrett Warnell, Gauraang Dhamankar, Anirudh Nair, Peter Stone:
APPL: Adaptive Planner Parameter Learning. Robotics Auton. Syst. 154: 104132 (2022) - [c435]Shahaf S. Shperberg, Bo Liu, Alessandro Allievi, Peter Stone:
A Rule-based Shield: Accumulating Safety Rules from Catastrophic Action Effects. CoLLAs 2022: 231-242 - [c434]Bo Liu, Qiang Liu, Peter Stone:
Continual Learning and Private Unlearning. CoLLAs 2022: 243-254 - [c433]Yifeng Zhu, Abhishek Joshi, Peter Stone, Yuke Zhu:
VIOLA: Object-Centric Imitation Learning for Vision-Based Robot Manipulation. CoRL 2022: 1199-1210 - [c432]Yoonchang Sung, Zizhao Wang, Peter Stone:
Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning. CoRL 2022: 2115-2124 - [c431]Jiaxun Cui, Hang Qiu, Dian Chen, Peter Stone, Yuke Zhu:
Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles. CVPR 2022: 17231-17241 - [c430]Kingsley Nweye, Zoltán Nagy, Bo Liu, Peter Stone:
Offline training of multi-agent reinforcement agents for grid-interactive buildings control. e-Energy 2022: 442-443 - [c429]Reuth Mirsky, Ignacio Carlucho, Arrasy Rahman, Elliot Fosong, William Macke, Mohan Sridharan, Peter Stone, Stefano V. Albrecht:
A Survey of Ad Hoc Teamwork Research. EUMAS 2022: 275-293 - [c428]Akarsh Kumar, Bo Liu, Risto Miikkulainen, Peter Stone:
Effective mutation rate adaptation through group elite selection. GECCO 2022: 721-729 - [c427]Zizhao Wang, Xuesu Xiao, Zifan Xu, Yuke Zhu, Peter Stone:
Causal Dynamics Learning for Task-Independent State Abstraction. ICML 2022: 23151-23180 - [c426]Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuke Zhu, Peter Stone, Shiqi Zhang:
Visually Grounded Task and Motion Planning for Mobile Manipulation. ICRA 2022: 1925-1931 - [c425]Haresh Karnan, Faraz Torabi, Garrett Warnell, Peter Stone:
Adversarial Imitation Learning from Video Using a State Observer. ICRA 2022: 2452-2458 - [c424]Eddy Hudson, Garrett Warnell, Faraz Torabi, Peter Stone:
Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch. ICRA 2022: 2482-2488 - [c423]Haresh Karnan, Garrett Warnell, Xuesu Xiao, Peter Stone:
VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation. ICRA 2022: 2497-2503 - [c422]Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone:
Dynamic Sparse Training for Deep Reinforcement Learning. IJCAI 2022: 3437-3443 - [c421]Haresh Karnan, Kavan Singh Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett Warnell, Peter Stone, Joydeep Biswas:
VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics. IROS 2022: 3294-3301 - [c420]Keya Ghonasgi, Reuth Mirsky, Adrian M. Haith, Peter Stone, Ashish D. Deshpande:
Quantifying Changes in Kinematic Behavior of a Human-Exoskeleton Interactive System. IROS 2022: 10734-10739 - [c419]Bo Liu, Mao Ye, Stephen Wright, Peter Stone, Qiang Liu:
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach. NeurIPS 2022 - [c418]James MacGlashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, Peter Stone:
Value Function Decomposition for Iterative Design of Reinforcement Learning Agents. NeurIPS 2022 - [c417]Sai Kiran Narayanaswami, Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit Narvekar, Peter Stone:
Towards a Real-Time, Low-Resource, End-to-End Object Detection Pipeline for Robot Soccer. RoboCup 2022: 62-74 - [c416]Anirudh Nair, Fulin Jiang, Kang Hou, Zifan Xu, Shuozhe Li, Xuesu Xiao, Peter Stone:
DynaBARN: Benchmarking Metric Ground Navigation in Dynamic Environments. SSRR 2022: 347-352 - [i117]Haresh Karnan, Garrett Warnell, Faraz Torabi, Peter Stone:
Adversarial Imitation Learning from Video using a State Observer. CoRR abs/2202.00243 (2022) - [i116]Shahaf S. Shperberg, Bo Liu, Peter Stone:
Learning a Shield from Catastrophic Action Effects: Never Repeat the Same Mistake. CoRR abs/2202.09516 (2022) - [i115]Reuth Mirsky, Ignacio Carlucho, Arrasy Rahman, Elliot Fosong, William Macke, Mohan Sridharan, Peter Stone, Stefano V. Albrecht:
A Survey of Ad Hoc Teamwork: Definitions, Methods, and Open Problems. CoRR abs/2202.10450 (2022) - [i114]Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuke Zhu, Peter Stone, Shiqi Zhang:
Visually Grounded Task and Motion Planning for Mobile Manipulation. CoRR abs/2202.10667 (2022) - [i113]Bo Liu, Qiang Liu, Peter Stone:
Continual Learning and Private Unlearning. CoRR abs/2203.12817 (2022) - [i112]Haresh Karnan, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Sören Pirk, Alexander Toshev, Justin W. Hart, Joydeep Biswas, Peter Stone:
Socially Compliant Navigation Dataset (SCAND): A Large-Scale Dataset of Demonstrations for Social Navigation. CoRR abs/2203.15041 (2022) - [i111]Haresh Karnan, Kavan Singh Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett Warnell, Peter Stone, Joydeep Biswas:
VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics. CoRR abs/2203.15983 (2022) - [i110]Akarsh Kumar, Bo Liu, Risto Miikkulainen, Peter Stone:
Effective Mutation Rate Adaptation through Group Elite Selection. CoRR abs/2204.04817 (2022) - [i109]Jiaxun Cui, Hang Qiu, Dian Chen, Peter Stone, Yuke Zhu:
COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehicles. CoRR abs/2205.02222 (2022) - [i108]Caroline Wang, Ishan Durugkar, Elad Liebman, Peter Stone:
DM2: Distributed Multi-Agent Reinforcement Learning for Distribution Matching. CoRR abs/2206.00233 (2022) - [i107]W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Allievi:
Models of human preference for learning reward functions. CoRR abs/2206.02231 (2022) - [i106]Pranav Atreya, Haresh Karnan, Kavan Singh Sikand, Xuesu Xiao, Garrett Warnell, Sadegh Rabiee, Peter Stone, Joydeep Biswas:
High-Speed Accurate Robot Control using Learned Forward Kinodynamics and Non-linear Least Squares Optimization. CoRR abs/2206.08487 (2022) - [i105]Zizhao Wang, Xuesu Xiao, Zifan Xu, Yuke Zhu, Peter Stone:
Causal Dynamics Learning for Task-Independent State Abstraction. CoRR abs/2206.13452 (2022) - [i104]James MacGlashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, Peter Stone:
Value Function Decomposition for Iterative Design of Reinforcement Learning Agents. CoRR abs/2206.13901 (2022) - [i103]Bo Liu, Yihao Feng, Qiang Liu, Peter Stone:
Metric Residual Networks for Sample Efficient Goal-conditioned Reinforcement Learning. CoRR abs/2208.08133 (2022) - [i102]Xuesu Xiao, Zifan Xu, Zizhao Wang, Yunlong Song, Garrett Warnell, Peter Stone, Tingnan Zhang, Shravan Ravi, Gary Wang, Haresh Karnan, Joydeep Biswas, Nicholas Mohammad, Lauren Bramblett, Rahul Peddi, Nicola Bezzo, Zhanteng Xie, Philip M. Dames:
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The BARN Challenge at ICRA 2022. CoRR abs/2208.10473 (2022) - [i101]Mao Ye, Bo Liu, Stephen Wright, Peter Stone, Qiang Liu:
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach. CoRR abs/2209.08709 (2022) - [i100]Jin Soo Park, Xuesu Xiao, Garrett Warnell, Harel Yedidsion, Peter Stone:
Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways. CoRR abs/2209.13641 (2022) - [i99]Zifan Xu, Bo Liu, Xuesu Xiao, Anirudh Nair, Peter Stone:
Benchmarking Reinforcement Learning Techniques for Autonomous Navigation. CoRR abs/2210.04839 (2022) - [i98]Zifan Xu, Anirudh Nair, Xuesu Xiao, Peter Stone:
Learning Real-world Autonomous Navigation by Self-Supervised Environment Synthesis. CoRR abs/2210.04852 (2022) - [i97]Vaibhav Bajaj, Guni Sharon, Peter Stone:
Task Phasing: Automated Curriculum Learning from Demonstrations. CoRR abs/2210.10999 (2022) - [i96]Yifeng Zhu, Abhishek Joshi, Peter Stone, Yuke Zhu:
VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors. CoRR abs/2210.11339 (2022) - [i95]Caroline Wang, Garrett Warnell, Peter Stone:
D-Shape: Demonstration-Shaped Reinforcement Learning via Goal Conditioning. CoRR abs/2210.14428 (2022) - [i94]Varun Raj Kompella, Thomas Walsh, Samuel Barrett, Peter R. Wurman, Peter Stone:
Event Tables for Efficient Experience Replay. CoRR abs/2211.00576 (2022) - [i93]Eddy Hudson, Ishan Durugkar, Garrett Warnell, Peter Stone:
ABC: Adversarial Behavioral Cloning for Offline Mode-Seeking Imitation Learning. CoRR abs/2211.04005 (2022) - [i92]Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David C. Parkes, William H. Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, Astro Teller:
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence. CoRR abs/2211.06318 (2022) - [i91]Yoonchang Sung, Zizhao Wang, Peter Stone:
Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning. CoRR abs/2211.07847 (2022) - [i90]Hager Radi, Josiah P. Hanna, Peter Stone, Matthew E. Taylor:
Safe Evaluation For Offline Learning: Are We Ready To Deploy? CoRR abs/2212.08302 (2022) - 2021
- [j98]Ruohan Zhang, Faraz Torabi, Garrett Warnell, Peter Stone:
Recent advances in leveraging human guidance for sequential decision-making tasks. Auton. Agents Multi Agent Syst. 35(2): 31 (2021) - [j97]Roberto Capobianco, Varun Raj Kompella, James Ault, Guni Sharon, Stacy Jong, Spencer J. Fox, Lauren Ancel Meyers, Peter R. Wurman, Peter Stone:
Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies. J. Artif. Intell. Res. 71: 953-992 (2021) - [j96]Josiah P. Hanna, Scott Niekum, Peter Stone:
Importance sampling in reinforcement learning with an estimated behavior policy. Mach. Learn. 110(6): 1267-1317 (2021) - [j95]Josiah P. Hanna, Siddharth Desai, Haresh Karnan, Garrett Warnell, Peter Stone:
Grounded action transformation for sim-to-real reinforcement learning. Mach. Learn. 110(9): 2469-2499 (2021) - [j94]Bo Liu, Xuesu Xiao, Peter Stone:
A Lifelong Learning Approach to Mobile Robot Navigation. IEEE Robotics Autom. Lett. 6(2): 1090-1096 (2021) - [j93]Xuesu Xiao, Bo Liu, Garrett Warnell, Peter Stone:
Toward Agile Maneuvers in Highly Constrained Spaces: Learning From Hallucination. IEEE Robotics Autom. Lett. 6(2): 1503-1510 (2021) - [j92]Xuesu Xiao, Joydeep Biswas, Peter Stone:
Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain. IEEE Robotics Autom. Lett. 6(3): 6054-6060 (2021) - [j91]Zizhao Wang, Xuesu Xiao, Garrett Warnell, Peter Stone:
APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback. IEEE Robotics Autom. Lett. 6(4): 7744-7749 (2021) - [j90]Peter Stone, Luca Iocchi, Flavio Tonidandel, Changjiu Zhou:
RoboCup 2021 Worldwide: A Successful Robotics Competition During a Pandemic [Competitions]. IEEE Robotics Autom. Mag. 28(4): 114-119 (2021) - [j89]Alec Koppel, Garrett Warnell, Ethan Stump, Peter Stone, Alejandro Ribeiro:
Policy Evaluation in Continuous MDPs With Efficient Kernelized Gradient Temporal Difference. IEEE Trans. Autom. Control. 66(4): 1856-1863 (2021) - [c415]Yu-Sian Jiang, Garrett Warnell, Peter Stone:
Goal Blending for Responsive Shared Autonomy in a Navigating Vehicle. AAAI 2021: 5939-5947 - [c414]Yuqian Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, Peter Stone:
Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks. AAAI 2021: 7995-8003 - [c413]William Macke, Reuth Mirsky, Peter Stone:
Expected Value of Communication for Planning in Ad Hoc Teamwork. AAAI 2021: 11290-11298 - [c412]Yuchen Cui, Qiping Zhang, Sahil Jain, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox:
Demonstration of the EMPATHIC Framework for Task Learning from Implicit Human Feedback. AAAI 2021: 16017-16019 - [c411]Reuth Mirsky, Peter Stone:
The Seeing-Eye Robot Grand Challenge: Rethinking Automated Care. AAMAS 2021: 28-33 - [c410]Jiaxun Cui, William Macke, Harel Yedidsion, Aastha Goyal, Daniel Urieli, Peter Stone:
Scalable Multiagent Driving Policies for Reducing Traffic Congestion. AAMAS 2021: 386-394 - [c409]Guni Sharon, James Ault, Peter Stone, Varun Raj Kompella, Roberto Capobianco:
Multiagent Epidemiologic Inference through Realtime Contact Tracing. AAMAS 2021: 1182-1190 - [c408]Peter Stone:
Efficient Robot Skill Learning: Grounded Simulation Learning and Imitation Learning from Observation. ICARSC 2021: 3 - [c407]Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar:
Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition. ICML 2021: 6860-6870 - [c406]Blake Holman, Abrar Anwar, Akash Singh, Mauricio Tec, Justin W. Hart, Peter Stone:
Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation. ICRA 2021: 3553-3559 - [c405]Zizhao Wang, Xuesu Xiao, Bo Liu, Garrett Warnell, Peter Stone:
APPLI: Adaptive Planner Parameter Learning From Interventions. ICRA 2021: 6079-6085 - [c404]Zifan Xu, Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Bo Liu, Zizhao Wang, Peter Stone:
APPLR: Adaptive Planner Parameter Learning from Reinforcement. ICRA 2021: 6086-6092 - [c403]Xuesu Xiao, Bo Liu, Peter Stone:
Agile Robot Navigation through Hallucinated Learning and Sober Deployment. ICRA 2021: 7316-7322 - [c402]Harel Yedidsion, Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, Peter Stone:
A Scavenger Hunt for Service Robots. ICRA 2021: 7774-7780 - [c401]Shih-Yun Lo, Benito Fernandez, Peter Stone, Andrea Lockerd Thomaz:
Towards Safe Motion Planning in Human Workspaces: A Robust Multi-agent Approach. ICRA 2021: 7929-7935 - [c400]Piyush Khandelwal, James MacGlashan, Peter R. Wurman, Peter Stone:
Efficient Real-Time Inference in Temporal Convolution Networks. ICRA 2021: 13489-13495 - [c399]Zizhao Wang, Xuesu Xiao, Alexander J. Nettekoven, Kadhiravan Umasankar, Anika Singh, Sriram Bommakanti, Ufuk Topcu, Peter Stone:
From Agile Ground to Aerial Navigation: Learning from Learned Hallucination. IROS 2021: 148-153 - [c398]Keya Ghonasgi, Reuth Mirsky, Sanmit Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, Ashish D. Deshpande:
Capturing Skill State in Curriculum Learning for Human Skill Acquisition. IROS 2021: 771-776 - [c397]Faraz Torabi, Garrett Warnell, Peter Stone:
DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation. IROS 2021: 2391-2397 - [c396]Bo Liu, Xuesu Xiao, Peter Stone:
Team Orienteering Coverage Planning with Uncertain Reward. IROS 2021: 9728-9733 - [c395]Ishan Durugkar, Mauricio Tec, Scott Niekum, Peter Stone:
Adversarial Intrinsic Motivation for Reinforcement Learning. NeurIPS 2021: 8622-8636 - [c394]Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, Qiang Liu:
Conflict-Averse Gradient Descent for Multi-task learning. NeurIPS 2021: 18878-18890 - [c393]Sihang Guo, Ruohan Zhang, Bo Liu, Yifeng Zhu, Dana H. Ballard, Mary M. Hayhoe, Peter Stone:
Machine versus Human Attention in Deep Reinforcement Learning Tasks. NeurIPS 2021: 25370-25385 - [c392]Patrick MacAlpine, Bo Liu, William Macke, Caroline Wang, Peter Stone:
UT Austin Villa: RoboCup 2021 3D Simulation League Competition Champions. RoboCup 2021: 314-326 - [c391]Zifan Xu, Xuesu Xiao, Garrett Warnell, Anirudh Nair, Peter Stone:
Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning. SSRR 2021: 217-222 - [i89]Lemeng Wu, Bo Liu, Peter Stone, Qiang Liu:
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks. CoRR abs/2102.08574 (2021) - [i88]Xuesu Xiao, Joydeep Biswas, Peter Stone:
Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain. CoRR abs/2102.12667 (2021) - [i87]Jiaxun Cui, William Macke, Harel Yedidsion, Aastha Goyal, Daniel Urieli, Peter Stone:
Scalable Multiagent Driving Policies For Reducing Traffic Congestion. CoRR abs/2103.00058 (2021) - [i86]William Macke, Reuth Mirsky, Peter Stone:
Expected Value of Communication for Planning in Ad Hoc Teamwork. CoRR abs/2103.01171 (2021) - [i85]Harel Yedidsion, Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, Peter Stone:
A Scavenger Hunt for Service Robots. CoRR abs/2103.05225 (2021) - [i84]Faraz Torabi, Garrett Warnell, Peter Stone:
DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation. CoRR abs/2104.00163 (2021) - [i83]Harel Yedidsion, Shani Alkoby, Peter Stone:
Sequential Online Chore Division for Autonomous Vehicle Convoy Formation. CoRR abs/2104.04159 (2021) - [i82]Eddy Hudson, Garrett Warnell, Faraz Torabi, Peter Stone:
Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch. CoRR abs/2104.07810 (2021) - [i81]W. Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone:
Reward (Mis)design for Autonomous Driving. CoRR abs/2104.13906 (2021) - [i80]Bo Liu, Xuesu Xiao, Peter Stone:
Team Orienteering Coverage Planning with Uncertain Reward. CoRR abs/2105.03721 (2021) - [i79]Eddy Hudson, Garrett Warnell, Peter Stone:
RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning. CoRR abs/2105.03756 (2021) - [i78]Xuesu Xiao, Zizhao Wang, Zifan Xu, Bo Liu, Garrett Warnell, Gauraang Dhamankar, Anirudh Nair, Peter Stone:
APPL: Adaptive Planner Parameter Learning. CoRR abs/2105.07620 (2021) - [i77]Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Animashree Anandkumar:
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition. CoRR abs/2105.08692 (2021) - [i76]Haresh Karnan, Garrett Warnell, Xuesu Xiao, Peter Stone:
VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation. CoRR abs/2105.09371 (2021) - [i75]Ishan Durugkar, Mauricio Tec, Scott Niekum, Peter Stone:
Adversarial Intrinsic Motivation for Reinforcement Learning. CoRR abs/2105.13345 (2021) - [i74]Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone:
Dynamic Sparse Training for Deep Reinforcement Learning. CoRR abs/2106.04217 (2021) - [i73]Reuth Mirsky, Xuesu Xiao, Justin W. Hart, Peter Stone:
Prevention and Resolution of Conflicts in Social Navigation - a Survey. CoRR abs/2106.12113 (2021) - [i72]Justin W. Hart, Reuth Mirsky, Xuesu Xiao, Peter Stone:
Incorporating Gaze into Social Navigation. CoRR abs/2107.04001 (2021) - [i71]Ruohan Zhang, Faraz Torabi, Garrett Warnell, Peter Stone:
Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks. CoRR abs/2107.05825 (2021) - [i70]Zizhao Wang, Xuesu Xiao, Alexander J. Nettekoven, Kadhiravan Umasankar, Anika Singh, Sriram Bommakanti, Ufuk Topcu, Peter Stone:
From Agile Ground to Aerial Navigation: Learning from Learned Hallucination. CoRR abs/2108.09793 (2021) - [i69]Zizhao Wang, Xuesu Xiao, Garrett Warnell, Peter Stone:
APPLE: Adaptive Planner Parameter Learning from Evaluative Feedback. CoRR abs/2108.09801 (2021) - [i68]Yifeng Zhu, Peter Stone, Yuke Zhu:
Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation. CoRR abs/2109.13841 (2021) - [i67]Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, Qiang Liu:
Conflict-Averse Gradient Descent for Multi-task Learning. CoRR abs/2110.14048 (2021) - [i66]Yulin Zhang, William Macke, Jiaxun Cui, Daniel Urieli, Peter Stone:
Learning a Robust Multiagent Driving Policy for Traffic Congestion Reduction. CoRR abs/2112.03759 (2021) - 2020
- [j88]Felipe Leno da Silva, Garrett Warnell, Anna Helena Reali Costa, Peter Stone:
Agents teaching agents: a survey on inter-agent transfer learning. Auton. Agents Multi Agent Syst. 34(1): 9 (2020) - [j87]Stefano V. Albrecht, Peter Stone, Michael P. Wellman:
Special issue on autonomous agents modelling other agents: Guest editorial. Artif. Intell. 285: 103292 (2020) - [j86]Dagmar Monett, Colin W. P. Lewis, Kristinn R. Thórisson, Joscha Bach, Gianluca Baldassarre, Giovanni Granato, Istvan S. N. Berkeley, François Chollet, Matthew Crosby, Henry Shevlin, John F. Sowa, John E. Laird, Shane Legg, Peter Lindes, Tomás Mikolov, William J. Rapaport, Raúl Rojas, Marek Rosa, Peter Stone, Richard S. Sutton, Roman V. Yampolskiy, Pei Wang, Roger C. Schank, Aaron Sloman, Alan F. T. Winfield:
Special Issue "On Defining Artificial Intelligence" - Commentaries and Author's Response. J. Artif. Gen. Intell. 11(2): 1-100 (2020) - [j85]Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin W. Hart, Peter Stone, Raymond J. Mooney:
Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog. J. Artif. Intell. Res. 67: 327-374 (2020) - [j84]Shih-Yun Lo, Shiqi Zhang, Peter Stone:
The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation. J. Artif. Intell. Res. 69: 471-500 (2020) - [j83]Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, Peter Stone:
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. J. Mach. Learn. Res. 21: 181:1-181:50 (2020) - [j82]Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, Peter Stone:
APPLD: Adaptive Planner Parameter Learning From Demonstration. IEEE Robotics Autom. Lett. 5(3): 4541-4547 (2020) - [j81]Brahma S. Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, Peter Stone:
RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration. IEEE Robotics Autom. Lett. 5(4): 6262-6269 (2020) - [c390]Varun Raj Kompella, Roberto Capobianco, Stacy Jong, Jonathan Browne, Spencer J. Fox, Lauren Ancel Meyers, Peter R. Wurman, Peter Stone:
Reinforcement Learning for Optimization of COVID-19 Mitigation Policies. AI4SG@AAAI Fall Symposium 2020 - [c389]Harel Yedidsion, Shani Alkoby, Peter Stone:
The Sequential Online Chore Division Problem - Definition and Application. AAMAS 2020: 2059-2061 - [c388]Felipe Leno da Silva, Garrett Warnell, Anna Helena Reali Costa, Peter Stone:
Agents Teaching Agents: A Survey on Inter-agent Transfer Learning. AAMAS 2020: 2165-2167 - [c387]Yuchen Cui, Qiping Zhang, W. Bradley Knox, Alessandro Allievi, Peter Stone, Scott Niekum:
The EMPATHIC Framework for Task Learning from Implicit Human Feedback. CoRL 2020: 604-626 - [c386]Jin Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, Peter Stone:
Learning to Improve Multi-Robot Hallway Navigation. CoRL 2020: 1883-1895 - [c385]Brahma S. Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone:
Reducing Sampling Error in Batch Temporal Difference Learning. ICML 2020: 7543-7552 - [c384]Reuth Mirsky, William Macke, Andy Wang, Harel Yedidsion, Peter Stone:
A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork. IJCAI 2020: 254-260 - [c383]Ishan Durugkar, Elad Liebman, Peter Stone:
Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning. IJCAI 2020: 2505-2511 - [c382]Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, Peter Stone:
Reinforced Grounded Action Transformation for Sim-to-Real Transfer. IROS 2020: 4397-4402 - [c381]Rishi Shah, Yuqian Jiang, Justin W. Hart, Peter Stone:
Deep R-Learning for Continual Area Sweeping. IROS 2020: 5542-5547 - [c380]Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, Peter Stone:
Stochastic Grounded Action Transformation for Robot Learning in Simulation. IROS 2020: 6106-6111 - [c379]Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone:
An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch. NeurIPS 2020 - [c378]Lemeng Wu, Bo Liu, Peter Stone, Qiang Liu:
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks. NeurIPS 2020 - [c377]Keting Lu, Shiqi Zhang, Peter Stone, Xiaoping Chen:
Learning and Reasoning for Robot Dialog and Navigation Tasks. SIGdial 2020: 107-117 - [c376]Justin W. Hart, Reuth Mirsky, Xuesu Xiao, Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, Peter Stone:
Using Human-Inspired Signals to Disambiguate Navigational Intentions. ICSR 2020: 320-331 - [c375]Daniel Perille, Abigail Truong, Xuesu Xiao, Peter Stone:
Benchmarking Metric Ground Navigation. SSRR 2020: 116-121 - [i65]Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, Peter Stone:
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. CoRR abs/2003.04960 (2020) - [i64]Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, Peter Stone:
APPLD: Adaptive Planner Parameter Learning from Demonstration. CoRR abs/2004.00116 (2020) - [i63]Shiqi Zhang, Peter Stone:
iCORPP: Interleaved Commonsense Reasoning and Probabilistic Planning on Robots. CoRR abs/2004.08672 (2020) - [i62]Keting Lu, Shiqi Zhang, Peter Stone, Xiaoping Chen:
Learning and Reasoning for Robot Dialog and Navigation Tasks. CoRR abs/2005.09833 (2020) - [i61]Rishi Shah, Yuqian Jiang, Justin W. Hart, Peter Stone:
Deep R-Learning for Continual Area Sweeping. CoRR abs/2006.00589 (2020) - [i60]Elad Liebman, Peter Stone:
Artificial Musical Intelligence: A Survey. CoRR abs/2006.10553 (2020) - [i59]Yuqian Jiang, Sudarshanan Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, Peter Stone:
Temporal-Logic-Based Reward Shaping for Continuing Learning Tasks. CoRR abs/2007.01498 (2020) - [i58]Xuesu Xiao, Bo Liu, Garrett Warnell, Peter Stone:
Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucination. CoRR abs/2007.14479 (2020) - [i57]Bo Liu, Xuesu Xiao, Peter Stone:
Lifelong Navigation. CoRR abs/2007.14486 (2020) - [i56]Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, Peter Stone:
Reinforced Grounded Action Transformation for Sim-to-Real Transfer. CoRR abs/2008.01279 (2020) - [i55]Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, Peter Stone:
Stochastic Grounded Action Transformation for Robot Learning in Simulation. CoRR abs/2008.01281 (2020) - [i54]Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone:
An Imitation from Observation Approach to Sim-to-Real Transfer. CoRR abs/2008.01594 (2020) - [i53]Brahma S. Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone:
Reducing Sampling Error in Batch Temporal Difference Learning. CoRR abs/2008.06738 (2020) - [i52]Daniel Perille, Abigail Truong, Xuesu Xiao, Peter Stone:
Benchmarking Metric Ground Navigation. CoRR abs/2008.13315 (2020) - [i51]Yuchen Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox:
The EMPATHIC Framework for Task Learning from Implicit Human Feedback. CoRR abs/2009.13649 (2020) - [i50]Yunshu Du, Garrett Warnell, Assefaw Hadish Gebremedhin, Peter Stone, Matthew E. Taylor:
Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy. CoRR abs/2009.13736 (2020) - [i49]Xuesu Xiao, Bo Liu, Peter Stone:
Agile Robot Navigation through Hallucinated Learning and Sober Deployment. CoRR abs/2010.08098 (2020) - [i48]Xuesu Xiao, Bo Liu, Peter Stone:
Extended Abstract: Motion Planners Learned from Geometric Hallucination. CoRR abs/2010.09158 (2020) - [i47]Varun Raj Kompella, Roberto Capobianco, Stacy Jong, Jonathan Browne, Spencer J. Fox, Lauren Ancel Meyers, Peter R. Wurman, Peter Stone:
Reinforcement Learning for Optimization of COVID-19 Mitigation policies. CoRR abs/2010.10560 (2020) - [i46]Ruohan Zhang, Bo Liu, Yifeng Zhu, Sihang Guo, Mary M. Hayhoe, Dana H. Ballard, Peter Stone:
Human versus Machine Attention in Deep Reinforcement Learning Tasks. CoRR abs/2010.15942 (2020) - [i45]Zifan Xu, Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Bo Liu, Zizhao Wang, Peter Stone:
APPLR: Adaptive Planner Parameter Learning from Reinforcement. CoRR abs/2011.00397 (2020) - [i44]Zizhao Wang, Xuesu Xiao, Bo Liu, Garrett Warnell, Peter Stone:
APPLI: Adaptive Planner Parameter Learning From Interventions. CoRR abs/2011.00400 (2020) - [i43]Xuesu Xiao, Bo Liu, Garrett Warnell, Peter Stone:
Motion Control for Mobile Robot Navigation Using Machine Learning: a Survey. CoRR abs/2011.13112 (2020)
2010 – 2019
- 2019
- [j80]Yuqian Jiang, Harel Yedidsion, Shiqi Zhang, Guni Sharon, Peter Stone:
Multi-robot planning with conflicts and synergies. Auton. Robots 43(8): 2011-2032 (2019) - [j79]Yuqian Jiang, Shiqi Zhang, Piyush Khandelwal, Peter Stone:
Task planning in robotics: an empirical comparison of PDDL- and ASP-based systems. Frontiers Inf. Technol. Electron. Eng. 20(3): 363-373 (2019) - [j78]Elad Liebman, Maytal Saar-Tsechansky, Peter Stone:
The Right Music at the Right Time: Adaptive Personalized Playlists Based on Sequence Modeling. MIS Q. 43(3) (2019) - [j77]Minoru Asada, Peter Stone, Manuela Veloso, Daniel D. Lee, Daniele Nardi:
RoboCup: A Treasure Trove of Rich Diversity for Research Issues and Interdisciplinary Connections [TC Spotlight]. IEEE Robotics Autom. Mag. 26(3): 99-102 (2019) - [c374]Josiah P. Hanna, Guni Sharon, Stephen D. Boyles, Peter Stone:
Selecting Compliant Agents for Opt-in Micro-Tolling. AAAI 2019: 565-572 - [c373]Shih-Yun Lo, Shani Alkoby, Peter Stone:
Robust Motion Planning and Safety Benchmarking in Human Workspaces. SafeAI@AAAI 2019 - [c372]Yuqian Jiang, Nick Walker, Justin W. Hart, Peter Stone:
Open-World Reasoning for Service Robots. ICAPS 2019: 725-733 - [c371]Sanmit Narvekar, Peter Stone:
Learning Curriculum Policies for Reinforcement Learning. AAMAS 2019: 25-33 - [c370]Josiah P. Hanna, Peter Stone:
Reducing Sampling Error in Policy Gradient Learning. AAMAS 2019: 1016-1024 - [c369]Guni Sharon, Stephen D. Boyles, Shani Alkoby, Peter Stone:
Marginal Cost Pricing with a Fixed Error Factor in Traffic Networks. AAMAS 2019: 1539-1546 - [c368]Shani Alkoby, Avilash Rath, Peter Stone:
Teaching Social Behavior through Human Reinforcement for Ad hoc Teamwork - The STAR Framework: Extended Abstract. AAMAS 2019: 1773-1775 - [c367]Jacob Menashe, Peter Stone:
Escape Room: A Configurable Testbed for Hierarchical Reinforcement Learning. AAMAS 2019: 2123-2125 - [c366]Faraz Torabi, Garrett Warnell, Peter Stone:
Adversarial Imitation Learning from State-only Demonstrations. AAMAS 2019: 2229-2231 - [c365]Felipe Leno da Silva, Anna Helena Reali Costa, Peter Stone:
Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games. BRACIS 2019: 479-484 - [c364]Josiah Hanna, Scott Niekum, Peter Stone:
Importance Sampling Policy Evaluation with an Estimated Behavior Policy. ICML 2019: 2605-2613 - [c363]Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin W. Hart, Peter Stone, Raymond J. Mooney:
Improving Grounded Natural Language Understanding through Human-Robot Dialog. ICRA 2019: 6934-6941 - [c362]Manish Ravula, Shani Alkoby, Peter Stone:
Ad Hoc Teamwork With Behavior Switching Agents. IJCAI 2019: 550-556 - [c361]Faraz Torabi, Garrett Warnell, Peter Stone:
Imitation Learning from Video by Leveraging Proprioception. IJCAI 2019: 3585-3591 - [c360]Faraz Torabi, Garrett Warnell, Peter Stone:
Recent Advances in Imitation Learning from Observation. IJCAI 2019: 6325-6331 - [c359]Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, Peter Stone:
Leveraging Human Guidance for Deep Reinforcement Learning Tasks. IJCAI 2019: 6339-6346 - [c358]Yuqian Jiang, Fangkai Yang, Shiqi Zhang, Peter Stone:
Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots. IROS 2019: 7529-7534 - [c357]Patrick MacAlpine, Faraz Torabi, Brahma S. Pavse, Peter Stone:
UT Austin Villa: RoboCup 2019 3D Simulation League Competition and Technical Challenge Champions. RoboCup 2019: 540-552 - [c356]Harel Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin W. Hart, Peter Stone, Raymond J. Mooney:
Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance. ICSR 2019: 133-143 - [i42]Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin W. Hart, Peter Stone, Raymond J. Mooney:
Improving Grounded Natural Language Understanding through Human-Robot Dialog. CoRR abs/1903.00122 (2019) - [i41]Faraz Torabi, Garrett Warnell, Peter Stone:
Imitation Learning from Video by Leveraging Proprioception. CoRR abs/1905.09335 (2019) - [i40]Faraz Torabi, Garrett Warnell, Peter Stone:
Recent Advances in Imitation Learning from Observation. CoRR abs/1905.13566 (2019) - [i39]Brahma S. Pavse, Faraz Torabi, Josiah P. Hanna, Garrett Warnell, Peter Stone:
RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration. CoRR abs/1906.07372 (2019) - [i38]Faraz Torabi, Sean Geiger, Garrett Warnell, Peter Stone:
Sample-efficient Adversarial Imitation Learning from Observation. CoRR abs/1906.07374 (2019) - [i37]Stefano V. Albrecht, Peter Stone:
Reasoning about Hypothetical Agent Behaviours and their Parameters. CoRR abs/1906.11064 (2019) - [i36]Nick Walker, Yuqian Jiang, Maya Cakmak, Peter Stone:
Desiderata for Planning Systems in General-Purpose Service Robots. CoRR abs/1907.02300 (2019) - [i35]Rishi Shah, Yuqian Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta, Rachel Schlossman, Marika Murphy, Justin W. Hart, Luis Sentis, Peter Stone:
Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report. CoRR abs/1909.06529 (2019) - [i34]Justin W. Hart, Reuth Mirsky, Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, Peter Stone:
Unclogging Our Arteries: Using Human-Inspired Signals to Disambiguate Navigational Intentions. CoRR abs/1909.06560 (2019) - [i33]Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, Peter Stone:
Leveraging Human Guidance for Deep Reinforcement Learning Tasks. CoRR abs/1909.09906 (2019) - 2018
- [j76]Patrick MacAlpine, Peter Stone:
Overlapping layered learning. Artif. Intell. 254: 21-43 (2018) - [j75]Stefano V. Albrecht, Peter Stone:
Autonomous agents modelling other agents: A comprehensive survey and open problems. Artif. Intell. 258: 66-95 (2018) - [j74]Barbara J. Grosz, Peter Stone:
A century-long commitment to assessing artificial intelligence and its impact on society. Commun. ACM 61(12): 68-73 (2018) - [j73]Ori Ossmy, Justine E. Hoch, Patrick MacAlpine, Shohan Hasan, Peter Stone, Karen E. Adolph:
Variety Wins: Soccer-Playing Robots and Infant Walking. Frontiers Neurorobotics 12: 19 (2018) - [c355]Elad Liebman, Eric Zavesky, Peter Stone:
Autonomous Model Management via Reinforcement Learning. AAAI Workshops 2018: 348-355 - [c354]Yu-Sian Jiang, Garrett Warnell, Peter Stone:
DIPD: Gaze-Based Intention Inference in Dynamic Environments. AAAI Workshops 2018: 614-621 - [c353]Haipeng Chen, Bo An, Guni Sharon, Josiah P. Hanna, Peter Stone, Chunyan Miao, Yeng Chai Soh:
DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation. AAAI 2018: 757-765 - [c352]Guni Sharon, Michael Albert, Tarun Rambha, Stephen D. Boyles, Peter Stone:
Traffic Optimization for a Mixture of Self-Interested and Compliant Agents. AAAI 2018: 1202-1209 - [c351]Garrett Warnell, Nicholas R. Waytowich, Vernon Lawhern, Peter Stone:
Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces. AAAI 2018: 1545-1554 - [c350]Jesse Thomason, Jivko Sinapov, Raymond J. Mooney, Peter Stone:
Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions. AAAI 2018: 5520-5527 - [c349]Ishan Durugkar, Peter Stone:
Adversarial Goal Generation for Intrinsic Motivation. AAAI 2018: 8073-8074 - [c348]Saeid Amiri, Suhua Wei, Shiqi Zhang, Jivko Sinapov, Jesse Thomason, Peter Stone:
Robot Behavioral Exploration and Multi-modal Perception using Dynamically Constructed Controllers. AAAI Spring Symposia 2018 - [c347]Josiah P. Hanna, Peter Stone:
Towards a Data Efficient Off-Policy Policy Gradient. AAAI Spring Symposia 2018 - [c346]Jacob Menashe, Peter Stone:
State Abstraction Synthesis for Discrete Models of Continuous Domains. AAAI Spring Symposia 2018 - [c345]Shih-Yun Lo, Shiqi Zhang, Peter Stone:
PETLON: Planning Efficiently for Task-Level-Optimal Navigation. AAMAS 2018: 220-228 - [c344]Elad Liebman, Eric Zavesky, Peter Stone:
A Stitch in Time - Autonomous Model Management via Reinforcement Learning. AAMAS 2018: 990-998 - [c343]Hamid Mirzaei, Guni Sharon, Stephen D. Boyles, Tony Givargis, Peter Stone:
Link-based Parameterized Micro-tolling Scheme for Optimal Traffic Management. AAMAS 2018: 2013-2015 - [c342]Aishwarya Padmakumar, Peter Stone, Raymond J. Mooney:
Learning a Policy for Opportunistic Active Learning. EMNLP 2018: 1347-1357 - [c341]Yu-Sian Jiang, Garrett Warnell, Peter Stone:
Inferring User Intention using Gaze in Vehicles. ICMI 2018: 298-306 - [c340]Saeid Amiri, Suhua Wei, Shiqi Zhang, Jivko Sinapov, Jesse Thomason, Peter Stone:
Multi-modal Predicate Identification using Dynamically Learned Robot Controllers. IJCAI 2018: 4638-4645 - [c339]Faraz Torabi, Garrett Warnell, Peter Stone:
Behavioral Cloning from Observation. IJCAI 2018: 4950-4957 - [c338]Justin W. Hart, Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, Peter Stone:
PRISM: Pose Registration for Integrated Semantic Mapping. IROS 2018: 896-902 - [c337]Hamid Mirzaei Buini, Guni Sharon, Stephen D. Boyles, Tony Givargis, Peter Stone:
Enhanced Delta-tolling: Traffic Optimization via Policy Gradient Reinforcement Learning. ISAIM 2018 - [c336]Guni Sharon, Michael Albert, Tarun Rambha, Stephen D. Boyles, Peter Stone:
Traffic Optimization For a Mixture of Self-interested and Compliant Agents. ISAIM 2018 - [c335]Elad Liebman, Corey N. White, Peter Stone:
On the Impact of Music on Decision Making in Cooperative Tasks. ISMIR 2018: 695-701 - [c334]Hamid Mirzaei, Guni Sharon, Stephen D. Boyles, Tony Givargis, Peter Stone:
Enhanced Delta-tolling: Traffic Optimization via Policy Gradient Reinforcement Learning. ITSC 2018: 47-52 - [c333]Rolando Fernandez, Nathan John, Sean Kirmani, Justin W. Hart, Jivko Sinapov, Peter Stone:
Passive Demonstrations of Light-Based Robot Signals for Improved Human Interpretability. RO-MAN 2018: 234-239 - [c332]Yu-Sian Jiang, Garrett Warnell, Eduardo Munera, Peter Stone:
A Study of Human-Robot Copilot Systems for En-route Destination Changing. RO-MAN 2018: 997-1004 - [c331]Patrick MacAlpine, Faraz Torabi, Brahma S. Pavse, John Sigmon, Peter Stone:
UT Austin Villa: RoboCup 2018 3D Simulation League Champions. RoboCup 2018: 462-475 - [i32]Yuqian Jiang, Shiqi Zhang, Piyush Khandelwal, Peter Stone:
An Empirical Comparison of PDDL-based and ASP-based Task Planners. CoRR abs/1804.08229 (2018) - [i31]Faraz Torabi, Garrett Warnell, Peter Stone:
Behavioral Cloning from Observation. CoRR abs/1805.01954 (2018) - [i30]Josiah Hanna, Scott Niekum, Peter Stone:
Importance Sampling Policy Evaluation with an Estimated Behavior Policy. CoRR abs/1806.01347 (2018) - [i29]Faraz Torabi, Garrett Warnell, Peter Stone:
Generative Adversarial Imitation from Observation. CoRR abs/1807.06158 (2018) - [i28]Barbara J. Grosz, Peter Stone:
A Century Long Commitment to Assessing Artificial Intelligence and its Impact on Society. CoRR abs/1808.07899 (2018) - [i27]Aishwarya Padmakumar, Peter Stone, Raymond J. Mooney:
Learning a Policy for Opportunistic Active Learning. CoRR abs/1808.10009 (2018) - [i26]Prabhat Nagarajan, Garrett Warnell, Peter Stone:
Deterministic Implementations for Reproducibility in Deep Reinforcement Learning. CoRR abs/1809.05676 (2018) - [i25]Shani Alkoby, Avilash Rath, Peter Stone:
Ad hoc Teamwork and Moral Feedback as a Framework for Safe Agent Behavior. CoRR abs/1809.07880 (2018) - [i24]Minkyu Kim, Miguel Arduengo, Nick Walker, Yuqian Jiang, Justin W. Hart, Peter Stone, Luis Sentis:
An Architecture for Person-Following using Active Target Search. CoRR abs/1809.08793 (2018) - [i23]Keting Lu, Shiqi Zhang, Peter Stone, Xiaoping Chen:
Robot Representing and Reasoning with Knowledge from Reinforcement Learning. CoRR abs/1809.11074 (2018) - [i22]Justin W. Hart, Harel Yedidsion, Yuqian Jiang, Nick Walker, Rishi Shah, Jesse Thomason, Aishwarya Padmakumar, Rolando Fernandez, Jivko Sinapov, Raymond J. Mooney, Peter Stone:
Interaction and Autonomy in RoboCup@Home and Building-Wide Intelligence. CoRR abs/1810.02919 (2018) - [i21]Yuqian Jiang, Nick Walker, Minkyu Kim, Nicolas Brissonneau, Daniel S. Brown, Justin W. Hart, Scott Niekum, Luis Sentis, Peter Stone:
LAAIR: A Layered Architecture for Autonomous Interactive Robots. CoRR abs/1811.03563 (2018) - [i20]Yuqian Jiang, Fangkai Yang, Shiqi Zhang, Peter Stone:
Integrating Task-Motion Planning with Reinforcement Learning for Robust Decision Making in Mobile Robots. CoRR abs/1811.08955 (2018) - [i19]Sanmit Narvekar, Peter Stone:
Learning Curriculum Policies for Reinforcement Learning. CoRR abs/1812.00285 (2018) - [i18]Jacob Menashe, Peter Stone:
Escape Room: A Configurable Testbed for Hierarchical Reinforcement Learning. CoRR abs/1812.09521 (2018) - 2017
- [j72]Stefano V. Albrecht, Somchaya Liemhetcharat, Peter Stone:
Special issue on multiagent interaction without prior coordination: guest editorial. Auton. Agents Multi Agent Syst. 31(4): 765-766 (2017) - [j71]Katie Genter, Tim Laue, Peter Stone:
Three years of the RoboCup standard platform league drop-in player competition - Creating and maintaining a large scale ad hoc teamwork robotics competition. Auton. Agents Multi Agent Syst. 31(4): 790-820 (2017) - [j70]Samuel Barrett, Avi Rosenfeld, Sarit Kraus, Peter Stone:
Making friends on the fly: Cooperating with new teammates. Artif. Intell. 242: 132-171 (2017) - [j69]Todd Hester, Peter Stone:
Intrinsically motivated model learning for developing curious robots. Artif. Intell. 247: 170-186 (2017) - [j68]Tsz-Chiu Au, Bikramjit Banerjee, Prithviraj Dasgupta, Peter Stone:
Multirobot Systems. IEEE Intell. Syst. 32(6): 3-5 (2017) - [j67]Piyush Khandelwal, Shiqi Zhang, Jivko Sinapov, Matteo Leonetti, Jesse Thomason, Fangkai Yang, Ilaria Gori, Maxwell Svetlik, Priyanka Khante, Vladimir Lifschitz, J. K. Aggarwal, Raymond J. Mooney, Peter Stone:
BWIBots: A platform for bridging the gap between AI and human-robot interaction research. Int. J. Robotics Res. 36(5-7): 635-659 (2017) - [j66]Matthew J. Hausknecht, Wen-Ke Li, Michael D. Mauk, Peter Stone:
Machine Learning Capabilities of a Simulated Cerebellum. IEEE Trans. Neural Networks Learn. Syst. 28(3): 510-522 (2017) - [c330]Michael Albert, Vincent Conitzer, Peter Stone:
Automated Design of Robust Mechanisms. AAAI 2017: 298-304 - [c329]Maxwell Svetlik, Matteo Leonetti, Jivko Sinapov, Rishi Shah, Nick Walker, Peter Stone:
Automatic Curriculum Graph Generation for Reinforcement Learning Agents. AAAI 2017: 2590-2596 - [c328]Josiah P. Hanna, Peter Stone:
Grounded Action Transformation for Robot Learning in Simulation. AAAI 2017: 3834-3840 - [c327]Shiqi Zhang, Piyush Khandelwal, Peter Stone:
Dynamically Constructed (PO)MDPs for Adaptive Robot Planning. AAAI 2017: 3855-3863 - [c326]Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, Peter Stone:
Designing Better Playlists with Monte Carlo Tree Search. AAAI 2017: 4715-4720 - [c325]Josiah P. Hanna, Peter Stone:
Grounded Action Transformation for Robot Learning in Simulation. AAAI 2017: 4931-4932 - [c324]Josiah P. Hanna, Peter Stone, Scott Niekum:
Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. AAAI 2017: 4933-4934 - [c323]Michael Albert, Vincent Conitzer, Peter Stone:
Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms? AAMAS 2017: 69-77 - [c322]Guni Sharon, Peter Stone:
A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections. AAMAS Workshops (Selected Papers) 2017: 151-167 - [c321]Patrick MacAlpine, Peter Stone:
Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges. AAMAS Workshops (Selected Papers) 2017: 168-186 - [c320]Shiqi Zhang, Yuqian Jiang, Guni Sharon, Peter Stone:
Multirobot Symbolic Planning under Temporal Uncertainty. AAMAS 2017: 501-510 - [c319]Katie Genter, Tim Laue, Peter Stone:
Three Years of the RoboCup Standard Platform League Drop-In Player Competition: Creating and Maintaining a Large Scale Ad Hoc Teamwork Robotics Competition. AAMAS 2017: 520-521 - [c318]Josiah P. Hanna, Peter Stone, Scott Niekum:
Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. AAMAS 2017: 538-546 - [c317]Stefano V. Albrecht, Peter Stone:
Reasoning about Hypothetical Agent Behaviours and their Parameters. AAMAS 2017: 547-555 - [c316]Piyush Khandelwal, Peter Stone:
Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests. AAMAS 2017: 1369-1377 - [c315]Katie Genter, Peter Stone:
Agent Behaviors for Joining and Leaving a Flock. AAMAS 2017: 1553-1555 - [c314]Elad Liebman, Eric Zavesky, Peter Stone:
Autonomous Model Management via Reinforcement Learning: Extended Abstract. AAMAS 2017: 1601-1603 - [c313]Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Justin W. Hart, Peter Stone, Raymond J. Mooney:
Opportunistic Active Learning for Grounding Natural Language Descriptions. CoRL 2017: 67-76 - [c312]Karl Tuyls, Peter Stone:
Multiagent Learning Paradigms. EUMAS/AT 2017: 3-21 - [c311]Santiago Gonzalez, Vijay Chidambaram, Jivko Sinapov, Peter Stone:
CC-Log: Drastically Reducing Storage Requirements for Robots Using Classification and Compression. HotStorage 2017 - [c310]Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum:
Data-Efficient Policy Evaluation Through Behavior Policy Search. ICML 2017: 1394-1403 - [c309]Sanmit Narvekar, Jivko Sinapov, Peter Stone:
Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning. IJCAI 2017: 2536-2542 - [c308]Dongcai Lu, Shiqi Zhang, Peter Stone, Xiaoping Chen:
Leveraging commonsense reasoning and multimodal perception for robot spoken dialog systems. IROS 2017: 6582-6588 - [c307]Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, Peter Stone:
Fast and Precise Black and White Ball Detection for RoboCup Soccer. RoboCup 2017: 45-58 - [c306]Patrick MacAlpine, Peter Stone:
UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions. RoboCup 2017: 473-485 - [r4]Peter Stone:
Q-Learning. Encyclopedia of Machine Learning and Data Mining 2017: 1033 - [r3]Peter Stone:
Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining 2017: 1088-1090 - [i17]Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum:
Data-Efficient Policy Evaluation Through Behavior Policy Search. CoRR abs/1706.03469 (2017) - [i16]Decebal Constantin Mocanu, Elena Mocanu, Peter Stone, Phuong H. Nguyen, Madeleine Gibescu, Antonio Liotta:
Evolutionary Training of Sparse Artificial Neural Networks: A Network Science Perspective. CoRR abs/1707.04780 (2017) - [i15]Stefano V. Albrecht, Peter Stone:
Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems. CoRR abs/1709.08071 (2017) - [i14]Guni Sharon, Michael Albert, Tarun Rambha, Stephen D. Boyles, Peter Stone:
Traffic Optimization For a Mixture of Self-interested and Compliant Agents. CoRR abs/1709.09569 (2017) - [i13]Garrett Warnell, Nicholas R. Waytowich, Vernon Lawhern, Peter Stone:
Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces. CoRR abs/1709.10163 (2017) - 2016
- [j65]Matteo Leonetti, Luca Iocchi, Peter Stone:
A synthesis of automated planning and reinforcement learning for efficient, robust decision-making. Artif. Intell. 241: 103-130 (2016) - [j64]Katie Genter, Patrick MacAlpine, Jacob Menashe, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, Peter Stone:
UT Austin Villa: Project-Driven Research in AI and Robotics. IEEE Intell. Syst. 31(2): 94-101 (2016) - [c305]Daniel Urieli, Peter Stone:
Autonomous Electricity Trading Using Time-of-Use Tariffs in a Competitive Market. AAAI 2016: 345-352 - [c304]Peter Stone:
What's Hot at RoboCup. AAAI 2016: 4346-4348 - [c303]Daniel Urieli, Peter Stone:
An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis. AAAI Workshop: AI for Smart Grids and Smart Buildings 2016 - [c302]Peter Stone:
Autonomous Learning Agents: Layered Learning and Ad Hoc Teamwork. AAMAS 2016: 2 - [c301]Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti, Peter Stone:
Source Task Creation for Curriculum Learning. AAMAS 2016: 566-574 - [c300]Katie Genter, Peter Stone:
Adding Influencing Agents to a Flock. AAMAS 2016: 615-623 - [c299]Daniel Urieli, Peter Stone:
An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis. AAMAS 2016: 827-835 - [c298]Patrick MacAlpine, Elad Liebman, Peter Stone:
Adaptation of Surrogate Tasks for Bipedal Walk Optimization. GECCO (Companion) 2016: 1275-1276 - [c297]Donghyun Kim, Steven Jens Jorgensen, Peter Stone, Luis Sentis:
Dynamic behaviors on the NAO robot with closed-loop whole body operational space control. Humanoids 2016: 1121-1128 - [c296]Piyush Khandelwal, Elad Liebman, Scott Niekum, Peter Stone:
On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search. ICML 2016: 1319-1328 - [c295]Guni Sharon, Josiah Hanna, Tarun Rambha, Michael Albert, Peter Stone, Stephen D. Boyles:
Delta-Tolling: Adaptive Tolling for Optimizing Traffic Throughput. ATT@IJCAI 2016 - [c294]Jivko Sinapov, Priyanka Khante, Maxwell Svetlik, Peter Stone:
Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors. IJCAI 2016: 3462-3468 - [c293]Jesse Thomason, Jivko Sinapov, Maxwell Svetlik, Peter Stone, Raymond J. Mooney:
Learning Multi-Modal Grounded Linguistic Semantics by Playing "I Spy". IJCAI 2016: 3477-3483 - [c292]Shiqi Zhang, Dongcai Lu, Xiaoping Chen, Peter Stone:
Robot Scavenger Hunt: A Standardized Framework for Evaluating Intelligent Mobile Robots. IJCAI 2016: 4276-4277 - [c291]Elad Liebman, Peter Stone, Corey N. White:
Impact of Music on Decision Making in Quantitative Tasks. ISMIR 2016: 661-667 - [c290]Patrick MacAlpine, Peter Stone:
UT Austin Villa RoboCup 3D Simulation Base Code Release. RoboCup 2016: 135-143 - [c289]Patrick MacAlpine, Peter Stone:
Prioritized Role Assignment for Marking. RoboCup 2016: 306-318 - [c288]Patrick MacAlpine, Peter Stone:
UT Austin Villa: RoboCup 2016 3D Simulation League Competition and Technical Challenges Champions. RoboCup 2016: 515-528 - [c287]Matthew J. Hausknecht, Peter Stone:
Deep Reinforcement Learning in Parameterized Action Space. ICLR (Poster) 2016 - [i12]Josiah P. Hanna, Peter Stone, Scott Niekum:
High Confidence Off-Policy Evaluation with Models. CoRR abs/1606.06126 (2016) - [i11]Decebal Constantin Mocanu, Maria Torres Vega, Eric Eaton, Peter Stone, Antonio Liotta:
Online Contrastive Divergence with Generative Replay: Experience Replay without Storing Data. CoRR abs/1610.05555 (2016) - 2015
- [j63]Elad Liebman, Benny Chor, Peter Stone:
Representative Selection in Nonmetric Datasets. Appl. Artif. Intell. 29(8): 807-838 (2015) - [j62]W. Bradley Knox, Peter Stone:
Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance. Artif. Intell. 225: 24-50 (2015) - [j61]Eric Eaton, Tom Dietterich, Maria L. Gini, Barbara J. Grosz, Charles L. Isbell Jr., Subbarao Kambhampati, Michael L. Littman, Francesca Rossi, Stuart Russell, Peter Stone, Toby Walsh, Michael J. Wooldridge:
Who speaks for AI? AI Matters 2(2): 4-14 (2015) - [c286]Shiqi Zhang, Peter Stone:
CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied to Dialog with a Mobile Robot. AAAI 2015: 1394-1400 - [c285]Samuel Barrett, Peter Stone:
Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork. AAAI 2015: 2010-2016 - [c284]Patrick MacAlpine, Eric Price, Peter Stone:
SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-Makespan for Formational Positioning. AAAI 2015: 2096-2102 - [c283]Patrick MacAlpine, Mike Depinet, Peter Stone:
UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning. AAAI 2015: 2842-2848 - [c282]Katie Genter, Peter Stone:
Placing Influencing Agents in a Flock. AAAI 2015: 4160-4161 - [c281]Matthew J. Hausknecht, Peter Stone:
The Impact of Determinism on Learning Atari 2600 Games. AAAI Workshop: Learning for General Competency in Video Games 2015 - [c280]Matthew J. Hausknecht, Peter Stone:
Deep Recurrent Q-Learning for Partially Observable MDPs. AAAI Fall Symposia 2015: 29-37 - [c279]Daniel Urieli, Peter Stone:
Autonomous Electricity Trading Using Time-Of-Use Tariffs in a Competitive Market. AAAI Fall Symposia 2015: 91-92 - [c278]Shiqi Zhang, Peter Stone:
CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied to Dialog with a Mobile Robot. AAAI Spring Symposia 2015 - [c277]Katie Genter, Shun Zhang, Peter Stone:
Determining Placements of Influencing Agents in a Flock. AAMAS 2015: 247-255 - [c276]Elad Liebman, Maytal Saar-Tsechansky, Peter Stone:
DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation. AAMAS 2015: 591-599 - [c275]Jivko Sinapov, Sanmit Narvekar, Matteo Leonetti, Peter Stone:
Learning Inter-Task Transferability in the Absence of Target Task Samples. AAMAS 2015: 725-733 - [c274]Jacob Menashe, Peter Stone:
Monte Carlo Hierarchical Model Learning. AAMAS 2015: 771-779 - [c273]Piyush Khandelwal, Samuel Barrett, Peter Stone:
Leading the Way: An Efficient Multi-robot Guidance System. AAMAS 2015: 1625-1633 - [c272]Fei Fang, Peter Stone, Milind Tambe:
Defender Strategies In Domains Involving Frequent Adversary Interaction. AAMAS 2015: 1663-1664 - [c271]Katie Genter, Tim Laue, Peter Stone:
The RoboCup 2014 SPL Drop-in Player Competition: Encouraging Teamwork without Pre-coordination. AAMAS 2015: 1745-1746 - [c270]Jacob Menashe, Peter Stone:
Monte Carlo Hierarchical Model Learning: (Doctoral Consortium). AAMAS 2015: 1985-1986 - [c269]Jesse Thomason, Shiqi Zhang, Raymond J. Mooney, Peter Stone:
Learning to Interpret Natural Language Commands through Human-Robot Dialog. IJCAI 2015: 1923-1929 - [c268]Fei Fang, Peter Stone, Milind Tambe:
When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing. IJCAI 2015: 2589-2595 - [c267]Katie Genter, Tim Laue, Peter Stone:
Benchmarking robot cooperation without pre-coordination in the RoboCup Standard Platform League drop-in player competition. IROS 2015: 3415-3420 - [c266]Elad Liebman, Peter Stone, Corey N. White:
How Music Alters Decision Making - Impact of Music Stimuli on Emotional Classification. ISMIR 2015: 793-799 - [c265]Shiqi Zhang, Fangkai Yang, Piyush Khandelwal, Peter Stone:
Mobile Robot Planning Using Action Language BC with an Abstraction Hierarchy. LPNMR 2015: 502-516 - [c264]Patrick MacAlpine, Josiah Hanna, Jason Liang, Peter Stone:
UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions. RoboCup 2015: 118-131 - [c263]David Leonardo Leottau, Javier Ruiz-del-Solar, Patrick MacAlpine, Peter Stone:
A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer. RoboCup 2015: 290-302 - [c262]Ilaria Gori, Jivko Sinapov, Priyanka Khante, Peter Stone, J. K. Aggarwal:
Robot-Centric Activity Recognition 'in the Wild'. ICSR 2015: 224-234 - [i10]Elad Liebman, Benny Chor, Peter Stone:
Representative Selection in Non Metric Datasets. CoRR abs/1502.07428 (2015) - [i9]Matthew J. Hausknecht, Peter Stone:
Deep Recurrent Q-Learning for Partially Observable MDPs. CoRR abs/1507.06527 (2015) - 2014
- [j60]Doran Chakraborty, Peter Stone:
Multiagent learning in the presence of memory-bounded agents. Auton. Agents Multi Agent Syst. 28(2): 182-213 (2014) - [j59]Daniele Nardi, Itsuki Noda, A. Fernando Ribeiro, Peter Stone, Oskar von Stryk, Manuela M. Veloso:
RoboCup Soccer Leagues. AI Mag. 35(3): 77-85 (2014) - [j58]Peter Stone, Patrick MacAlpine, Katie Genter, Samuel Barrett:
Drop-in games at RoboCup. AI Matters 1(1): 20-22 (2014) - [j57]Matthew J. Hausknecht, Joel Lehman, Risto Miikkulainen, Peter Stone:
A Neuroevolution Approach to General Atari Game Playing. IEEE Trans. Comput. Intell. AI Games 6(4): 355-366 (2014) - [c261]Daniel Urieli, Peter Stone:
TacTex'13: A Champion Adaptive Power Trading Agent. AAAI 2014: 465-471 - [c260]Piyush Khandelwal, Peter Stone:
Leading the Way: An Efficient Multi-Robot Guidance System. AAAI Fall Symposia 2014 - [c259]Piyush Khandelwal, Peter Stone:
Multi-Robot Human Guidance Using Topological Graphs. AAAI Spring Symposia 2014 - [c258]Fangkai Yang, Piyush Khandelwal, Matteo Leonetti, Peter Stone:
Planning in Answer Set Programming while Learning Action Costs for Mobile Robots. AAAI Spring Symposia 2014 - [c257]Piyush Khandelwal, Fangkai Yang, Matteo Leonetti, Vladimir Lifschitz, Peter Stone:
Planning in Action Language BC while Learning Action Costs for Mobile Robots. ICAPS 2014 - [c256]Katie Long Genter, Peter Stone:
Influencing a Flock via Ad Hoc Teamwork. ANTS Conference 2014: 110-121 - [c255]Noa Agmon, Samuel Barrett, Peter Stone:
Modeling uncertainty in leading ad hoc teams. AAMAS 2014: 397-404 - [c254]Samuel Barrett, Noa Agmon, Noam Hazon, Sarit Kraus, Peter Stone:
Communicating with unknown teammates. AAMAS 2014: 1433-1434 - [c253]Daniel Urieli, Peter Stone:
TacTex'13: a champion adaptive power trading agent. AAMAS 2014: 1447-1448 - [c252]Tsz-Chiu Au, Shun Zhang, Peter Stone:
Semi-autonomous intersection management. AAMAS 2014: 1451-1452 - [c251]Patrick MacAlpine, Katie Long Genter, Samuel Barrett, Peter Stone:
The RoboCup 2013 drop-in player challenges: a testbed for ad hoc teamwork. AAMAS 2014: 1461-1462 - [c250]Patrick MacAlpine, Eric Price, Peter Stone:
SCRAM: scalable collision-avoiding role assignment with minimal-makespan for formational positioning. AAMAS 2014: 1463-1464 - [c249]Katie Genter, Peter Stone:
Orienting a flock via ad hoc teamwork. AAMAS 2014: 1543-1544 - [c248]Samuel Barrett, Noa Agmon, Noam Hazon, Sarit Kraus, Peter Stone:
Communicating with Unknown Teammates. ECAI 2014: 45-50 - [c247]Patrick MacAlpine, Katie Genter, Samuel Barrett, Peter Stone:
The RoboCup 2013 drop-in player challenges: Experiments in ad hoc teamwork. IROS 2014: 382-387 - [c246]Patrick MacAlpine, Mike Depinet, Jason Liang, Peter Stone:
UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions. RoboCup 2014: 33-46 - [c245]Mike Depinet, Patrick MacAlpine, Peter Stone:
Keyframe Sampling, Optimization, and Behavior Integration: Towards Long-Distance Kicking in the RoboCup 3D Simulation League. RoboCup 2014: 571-582 - [e5]Carla E. Brodley, Peter Stone:
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27 -31, 2014, Québec City, Québec, Canada. AAAI Press 2014, ISBN 978-1-57735-661-5 [contents] - [i8]Elad Liebman, Peter Stone:
DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation. CoRR abs/1401.1880 (2014) - 2013
- [j56]Peter Stone, Gal A. Kaminka, Sarit Kraus, Jeffrey S. Rosenschein, Noa Agmon:
Teaching and leading an ad hoc teammate: Collaboration without pre-coordination. Artif. Intell. 203: 35-65 (2013) - [j55]Todd Hester, Peter Stone:
TEXPLORE: real-time sample-efficient reinforcement learning for robots. Mach. Learn. 90(3): 385-429 (2013) - [j54]Wen-Ke Li, Matthew J. Hausknecht, Peter Stone, Michael D. Mauk:
Using a million cell simulation of the cerebellum: Network scaling and task generality. Neural Networks 47: 95-102 (2013) - [c244]Samuel Barrett, Peter Stone, Sarit Kraus, Avi Rosenfeld:
Teamwork with Limited Knowledge of Teammates. AAAI 2013: 102-108 - [c243]Alon Farchy, Samuel Barrett, Patrick MacAlpine, Peter Stone:
Humanoid robots learning to walk faster: from the real world to simulation and back. AAMAS 2013: 39-46 - [c242]Katie Long Genter, Noa Agmon, Peter Stone:
Ad hoc teamwork for leading a flock. AAMAS 2013: 531-538 - [c241]Todd Hester, Manuel Lopes, Peter Stone:
Learning exploration strategies in model-based reinforcement learning. AAMAS 2013: 1069-1076 - [c240]Doran Chakraborty, Peter Stone:
Cooperating with a markovian ad hoc teammate. AAMAS 2013: 1085-1092 - [c239]Daniel Urieli, Peter Stone:
A learning agent for heat-pump thermostat control. AAMAS 2013: 1093-1100 - [c238]Dustin Carlino, Stephen D. Boyles, Peter Stone:
Auction-based autonomous intersection management. ITSC 2013: 529-534 - [c237]W. Bradley Knox, Peter Stone, Cynthia Breazeal:
Teaching agents with human feedback: a demonstration of the TAMER framework. IUI Companion 2013: 65-66 - [c236]W. Bradley Knox, Peter Stone:
Learning non-myopically from human-generated reward. IUI 2013: 191-202 - [c235]Daniel Urieli, Peter Stone:
Model-Selection for Non-parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System. ECML/PKDD (1) 2013: 65-80 - [c234]Todd Hester, Peter Stone:
The Open-Source TEXPLORE Code Release for Reinforcement Learning on Robots. RoboCup 2013: 536-543 - [c233]Samuel Barrett, Katie Long Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, Peter Stone:
The 2012 UT Austin Villa Code Release. RoboCup 2013: 552-559 - [c232]W. Bradley Knox, Peter Stone, Cynthia Breazeal:
Training a Robot via Human Feedback: A Case Study. ICSR 2013: 460-470 - [e4]Xiaoping Chen, Peter Stone, Luis Enrique Sucar, Tijn van der Zant:
RoboCup 2012: Robot Soccer World Cup XVI [papers from the 16th Annual RoboCup International Symposium, Mexico City, Mexico, June 18-24, 2012]. Lecture Notes in Computer Science 7500, Springer 2013, ISBN 978-3-642-39249-8 [contents] - 2012
- [j53]Liz Sonenberg, Peter Stone, Kagan Tumer, Pinar Yolum:
Ten Years of AAMAS: Introduction to the Special Issue. AI Mag. 33(3): 11-13 (2012) - [j52]W. Bradley Knox, Brian D. Glass, Bradley C. Love, W. Todd Maddox, Peter Stone:
How Humans Teach Agents - A New Experimental Perspective. Int. J. Soc. Robotics 4(4): 409-421 (2012) - [c231]Patrick MacAlpine, Francisco Barrera, Peter Stone:
Positioning to Win: A Dynamic Role Assignment and Formation Positioning System. MAPF@AAAI 2012 - [c230]Patrick MacAlpine, Samuel Barrett, Daniel Urieli, Victor Vu, Peter Stone:
Design and Optimization of an Omnidirectional Humanoid Walk: A Winning Approach at the RoboCup 2011 3D Simulation Competition. AAAI 2012: 1047-1053 - [c229]Todd Hester, Peter Stone:
TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots. AAAI Spring Symposium: Designing Intelligent Robots 2012 - [c228]Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae Stiurca, Victor Vu, Peter Stone:
UT Austin Villa 2011: a champion agent in the RoboCup 3D soccer simulation competition. AAMAS 2012: 129-136 - [c227]Noa Agmon, Peter Stone:
Leading ad hoc agents in joint action settings with multiple teammates. AAMAS 2012: 341-348 - [c226]Samuel Barrett, Peter Stone:
An analysis framework for ad hoc teamwork tasks. AAMAS 2012: 357-364 - [c225]W. Bradley Knox, Peter Stone:
Reinforcement learning from simultaneous human and MDP reward. AAMAS 2012: 475-482 - [c224]Katie Long Genter, Noa Agmon, Peter Stone:
Role selection in ad hoc teamwork. AAMAS 2012: 1251-1252 - [c223]Matthew J. Hausknecht, Piyush Khandelwal, Risto Miikkulainen, Peter Stone:
HyperNEAT-GGP: a hyperNEAT-based atari general game player. GECCO 2012: 217-224 - [c222]Chien-Liang Fok, Maykel Hanna, Seth Gee, Tsz-Chiu Au, Peter Stone, Christine Julien, Sriram Vishwanath:
A Platform for Evaluating Autonomous Intersection Management Policies. ICCPS 2012: 87-96 - [c221]Todd Hester, Peter Stone:
Intrinsically motivated model learning for a developing curious agent. ICDL-EPIROB 2012: 1-6 - [c220]Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, Peter Stone:
PAC Subset Selection in Stochastic Multi-armed Bandits. ICML 2012 - [c219]Todd Hester, Michael J. Quinlan, Peter Stone:
RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for robot control. ICRA 2012: 85-90 - [c218]Noa Agmon, Chien-Liang Fok, Yehuda Emaliah, Peter Stone, Christine Julien, Sriram Vishwanath:
On coordination in practical multi-robot patrol. ICRA 2012: 650-656 - [c217]Tsz-Chiu Au, Michael J. Quinlan, Peter Stone:
Setpoint scheduling for autonomous vehicle controllers. ICRA 2012: 2055-2060 - [c216]Tsz-Chiu Au, Chien-Liang Fok, Sriram Vishwanath, Christine Julien, Peter Stone:
Evasion planning for autonomous vehicles at intersections. IROS 2012: 1541-1546 - [c215]Manuela M. Veloso, Peter Stone:
Video: RoboCup robot soccer history 1997 - 2011. IROS 2012: 5452-5453 - [c214]Dustin Carlino, Mike Depinet, Piyush Khandelwal, Peter Stone:
Approximately Orchestrated Routing and Transportation Analyzer: Large-scale traffic simulation for autonomous vehicles. ITSC 2012: 334-339 - [c213]W. Bradley Knox, Peter Stone:
Reinforcement learning from human reward: Discounting in episodic tasks. RO-MAN 2012: 878-885 - [c212]Samuel Barrett, Katie Long Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, Peter Stone:
UT Austin Villa 2012: Standard Platform League World Champions. RoboCup 2012: 36-47 - [c211]Patrick MacAlpine, Nick Collins, Adrian Lopez-Mobilia, Peter Stone:
UT Austin Villa: RoboCup 2012 3D Simulation League Champion. RoboCup 2012: 77-88 - [c210]Patrick MacAlpine, Francisco Barrera, Peter Stone:
Positioning to Win: A Dynamic Role Assignment and Formation Positioning System. RoboCup 2012: 190-201 - [p3]Todd Hester, Peter Stone:
Learning and Using Models. Reinforcement Learning 2012: 111-141 - [i7]Tobias Jung, Daniel Polani, Peter Stone:
Empowerment for Continuous Agent-Environment Systems. CoRR abs/1201.6583 (2012) - [i6]Tobias Jung, Peter Stone:
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-like Exploration. CoRR abs/1201.6604 (2012) - [i5]Tobias Jung, Peter Stone:
Feature Selection for Value Function Approximation Using Bayesian Model Selection. CoRR abs/1201.6615 (2012) - 2011
- [j51]Tobias Jung, Daniel Polani, Peter Stone:
Empowerment for continuous agent - environment systems. Adapt. Behav. 19(1): 16-39 (2011) - [j50]Matthew E. Taylor, Peter Stone:
An Introduction to Intertask Transfer for Reinforcement Learning. AI Mag. 32(1): 15-34 (2011) - [j49]Shivaram Kalyanakrishnan, Peter Stone:
Characterizing reinforcement learning methods through parameterized learning problems. Mach. Learn. 84(1-2): 205-247 (2011) - [j48]David Pardoe, Peter Stone:
Designing adaptive trading agents. SIGecom Exch. 10(2): 37-39 (2011) - [c209]Noa Agmon, Peter Stone:
Leading Multiple Ad Hoc Teammates in Joint Action Settings. Interactive Decision Theory and Game Theory 2011 - [c208]Raz Lin, Sarit Kraus, Noa Agmon, Samuel Barrett, Peter Stone:
Comparing Agents' Success against People in Security Domains. AAAI 2011: 809-814 - [c207]Noa Agmon, Daniel Urieli, Peter Stone:
Multiagent Patrol Generalized to Complex Environmental Conditions. AAAI 2011: 1090-1095 - [c206]Tsz-Chiu Au, Neda Shahidi, Peter Stone:
Enforcing Liveness in Autonomous Traffic Management. AAAI 2011: 1317-1322 - [c205]Samuel Barrett, Peter Stone:
Ad Hoc Teamwork in Variations of the Pursuit Domain. AAAI 2011: 1758-1759 - [c204]Katie Long Genter, Noa Agmon, Peter Stone:
Role-Based Ad Hoc Teamwork. AAAI 2011: 1782-1783 - [c203]Katie Long Genter, Noa Agmon, Peter Stone:
Role-Based Ad Hoc Teamwork. Plan, Activity, and Intent Recognition 2011 - [c202]W. Bradley Knox, Adam Bradley Setapen, Peter Stone:
Reinforcement Learning with Human Feedback in Mountain Car. AAAI Spring Symposium: Help Me Help You: Bridging the Gaps in Human-Agent Collaboration 2011 - [c201]Peter Stone:
Intersections of the Future: Using Fully Autonomous Vehicles. ADMI 2011: 3 - [c200]Shivaram Kalyanakrishnan, Peter Stone:
On learning with imperfect representations. ADPRL 2011: 17-24 - [c199]Shimon Whiteson, Brian Tanner, Matthew E. Taylor, Peter Stone:
Protecting against evaluation overfitting in empirical reinforcement learning. ADPRL 2011: 120-127 - [c198]Paul Scerri, Balajee Kannan, Prasanna Velagapudi, Kate Macarthur, Peter Stone, Matthew E. Taylor, John M. Dolan, Alessandro Farinelli, Archie C. Chapman, Bernadine Dias, George Kantor:
Flood Disaster Mitigation: A Real-World Challenge Problem for Multi-agent Unmanned Surface Vehicles. AAMAS Workshops 2011: 252-269 - [c197]Samuel Barrett, Peter Stone, Sarit Kraus:
Empirical evaluation of ad hoc teamwork in the pursuit domain. AAMAS 2011: 567-574 - [c196]Daniel Urieli, Patrick MacAlpine, Shivaram Kalyanakrishnan, Yinon Bentor, Peter Stone:
On optimizing interdependent skills: a case study in simulated 3D humanoid robot soccer. AAMAS 2011: 769-776 - [c195]David Pardoe, Peter Stone:
A particle filter for bid estimation in ad auctions with periodic ranking observations. AAMAS 2011: 887-894 - [c194]Noa Agmon, Daniel Urieli, Peter Stone:
Ship patrol: multiagent patrol under complex environmental conditions. AAMAS 2011: 1103-1104 - [c193]Neda Shahidi, Tsz-Chiu Au, Peter Stone:
Batch reservations in autonomous intersection management. AAMAS 2011: 1225-1226 - [c192]Peter Stone:
Invited Talk: PRISM - Practical RL: Representation, Interaction, Synthesis, and Mortality. EWRL 2011: 3 - [c191]Doran Chakraborty, Peter Stone:
Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree. ICML 2011: 737-744 - [c190]Matthew J. Hausknecht, Tsz-Chiu Au, Peter Stone:
Autonomous Intersection Management: Multi-intersection optimization. IROS 2011: 4581-4586 - [c189]Matthew J. Hausknecht, Tsz-Chiu Au, Peter Stone, David Fajardo, S. Travis Waller:
Dynamic lane reversal in traffic management. ITSC 2011: 1929-1934 - [c188]Aijun Bai, Xiaoping Chen, Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Peter Stone:
WrightEagle and UT Austin Villa: RoboCup 2011 Simulation League Champions. RoboCup 2011: 1-12 - [c187]Piyush Khandelwal, Peter Stone:
A Low Cost Ground Truth Detection System for RoboCup Using the Kinect. RoboCup 2011: 515-527 - [e3]Liz Sonenberg, Peter Stone, Kagan Tumer, Pinar Yolum:
10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), Taipei, Taiwan, May 2-6, 2011, Volume 1-3. IFAAMAS 2011, ISBN 978-0-9826571-5-7 [contents] - [i4]Todd Hester, Michael J. Quinlan, Peter Stone:
A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control. CoRR abs/1105.1749 (2011) - [i3]Michael J. Kearns, Michael L. Littman, Satinder Singh, Peter Stone:
ATTac-2000: An Adaptive Autonomous Bidding Agent. CoRR abs/1106.0678 (2011) - [i2]János A. Csirik, Michael L. Littman, David A. McAllester, Robert E. Schapire, Peter Stone:
Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions. CoRR abs/1106.5270 (2011) - 2010
- [j47]Shimon Whiteson, Matthew E. Taylor, Peter Stone:
Critical factors in the empirical performance of temporal difference and evolutionary methods for reinforcement learning. Auton. Agents Multi Agent Syst. 21(1): 1-35 (2010) - [j46]Jonathan Wildstrom, Peter Stone, Emmett Witchel:
Autonomous return on investment analysis of additional processing resources. Int. J. Auton. Comput. 1(3): 280-296 (2010) - [j45]David Pardoe, Peter Stone, Maytal Saar-Tsechansky, Tayfun Keskin, Kerem Tomak:
Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge. INFORMS J. Comput. 22(3): 353-370 (2010) - [c186]Tsz-Chiu Au, Peter Stone:
Motion Planning Algorithms for Autonomous Intersection Management. Bridging the Gap Between Task and Motion Planning 2010 - [c185]Peter Stone, Gal A. Kaminka, Sarit Kraus, Jeffrey S. Rosenschein:
Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination. AAAI 2010: 1504-1509 - [c184]W. Bradley Knox, Peter Stone:
Combining manual feedback with subsequent MDP reward signals for reinforcement learning. AAMAS 2010: 5-12 - [c183]Peter Stone, Sarit Kraus:
To teach or not to teach?: decision making under uncertainty in ad hoc teams. AAMAS 2010: 117-124 - [c182]David Pardoe, Doran Chakraborty, Peter Stone:
TacTex09: a champion bidding agent for ad auctions. AAMAS 2010: 1273-1280 - [c181]Adam Setapen, Michael J. Quinlan, Peter Stone:
MARIOnET: motion acquisition for robots through iterative online evaluative training. AAMAS 2010: 1435-1436 - [c180]Doran Chakraborty, Peter Stone:
Online model learning in adversarial Markov decision processes. AAMAS 2010: 1583-1584 - [c179]W. Bradley Knox, Peter Stone:
Training a Tetris agent via interactive shaping: a demonstration of the TAMER framework. AAMAS 2010: 1767-1768 - [c178]Todd Hester, Peter Stone:
Real time targeted exploration in large domains. ICDL 2010: 191-196 - [c177]Doran Chakraborty, Peter Stone:
Convergence, Targeted Optimality, and Safety in Multiagent Learning. ICML 2010: 191-198 - [c176]Shivaram Kalyanakrishnan, Peter Stone:
Efficient Selection of Multiple Bandit Arms: Theory and Practice. ICML 2010: 511-518 - [c175]David Pardoe, Peter Stone:
Boosting for Regression Transfer. ICML 2010: 863-870 - [c174]Todd Hester, Michael J. Quinlan, Peter Stone:
Generalized model learning for Reinforcement Learning on a humanoid robot. ICRA 2010: 2369-2374 - [c173]Michael J. Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, Peter Stone:
Bringing simulation to life: A mixed reality autonomous intersection. IROS 2010: 6083-6088 - [c172]Tobias Jung, Peter Stone:
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration. ECML/PKDD (1) 2010: 601-616 - [c171]Matthew J. Hausknecht, Peter Stone:
Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker. RoboCup 2010: 254-265 - [p2]Itsuki Noda, Peter Stone, Tomohisa Yamashita, Koichi Kurumatani:
Multi-Agent Social Simulation. Handbook of Ambient Intelligence and Smart Environments 2010: 703-729 - [r2]Peter Stone:
Q-Learning. Encyclopedia of Machine Learning 2010: 819 - [r1]Peter Stone:
Reinforcement Learning. Encyclopedia of Machine Learning 2010: 849-851
2000 – 2009
- 2009
- [j44]Matthew E. Taylor, Peter Stone:
Transfer Learning for Reinforcement Learning Domains: A Survey. J. Mach. Learn. Res. 10: 1633-1685 (2009) - [j43]Mohan Sridharan, Peter Stone:
Color learning and illumination invariance on mobile robots: A survey. Robotics Auton. Syst. 57(6-7): 629-644 (2009) - [c170]Ian R. Fasel, Michael J. Quinlan, Peter Stone:
A Task Specification Language for Bootstrap Learning. AAAI Spring Symposium: Agents that Learn from Human Teachers 2009: 48-55 - [c169]W. Bradley Knox, Ian R. Fasel, Peter Stone:
Design Principles for Creating Human-Shapable Agents. AAAI Spring Symposium: Agents that Learn from Human Teachers 2009: 79-86 - [c168]Peter Stone, Gal A. Kaminka, Jeffrey S. Rosenschein:
Leading a Best-Response Teammate in an Ad Hoc Team. AMEC/TADA 2009: 132-146 - [c167]Todd Hester, Peter Stone:
Generalized model learning for reinforcement learning in factored domains. AAMAS (2) 2009: 717-724 - [c166]Shivaram Kalyanakrishnan, Peter Stone:
An empirical analysis of value function-based and policy search reinforcement learning. AAMAS (2) 2009: 749-756 - [c165]Ian R. Fasel, Michael J. Quinlan, Peter Stone:
A task specification language for bootstrap learning. AAMAS (2) 2009: 1169-1170 - [c164]Shivaram Kalyanakrishnan, Peter Stone:
Learning complementary multiagent behaviors: a case study. AAMAS (2) 2009: 1359-1360 - [c163]Peter Djeu, Michael J. Quinlan, Peter Stone:
Improving particle filter performance using SSE instructions. IROS 2009: 3480-3485 - [c162]W. Bradley Knox, Peter Stone:
Interactively shaping agents via human reinforcement: the TAMER framework. K-CAP 2009: 9-16 - [c161]Nicholas K. Jong, Peter Stone:
Compositional Models for Reinforcement Learning. ECML/PKDD (1) 2009: 644-659 - [c160]Tobias Jung, Peter Stone:
Feature Selection for Value Function Approximation Using Bayesian Model Selection. ECML/PKDD (1) 2009: 660-675 - [c159]Shivaram Kalyanakrishnan, Todd Hester, Michael J. Quinlan, Yinon Bentor, Peter Stone:
Three Humanoid Soccer Platforms: Comparison and Synthesis. RoboCup 2009: 140-152 - [c158]Shivaram Kalyanakrishnan, Peter Stone:
Learning Complementary Multiagent Behaviors: A Case Study. RoboCup 2009: 153-165 - [p1]Kurt M. Dresner, Peter Stone, Mark Van Middlesworth:
An Unmanaged Intersection Protocol and Improved Intersection Safety for Autonomous Vehicles. Multi-Agent Systems for Traffic and Transportation Engineering 2009: 193-217 - 2008
- [j42]Daniel Stronger, Peter Stone:
Polynomial Regression with Automated Degree: a Function Approximator for Autonomous Agents. Int. J. Artif. Intell. Tools 17(1): 159-174 (2008) - [j41]Kurt M. Dresner, Peter Stone:
A Multiagent Approach to Autonomous Intersection Management. J. Artif. Intell. Res. 31: 591-656 (2008) - [j40]Michael P. Wellman, Amy Greenwald, Peter Stone:
Book announcement: autonomous bidding agents. SIGecom Exch. 7(2) (2008) - [c157]Matthew E. Taylor, Gregory Kuhlmann, Peter Stone:
Transfer Learning and Intelligence: an Argument and Approach. AGI 2008: 326-337 - [c156]David Pardoe, Peter Stone:
The 2007 TAC SCM Prediction Challenge. AMEC/TADA 2008: 175-189 - [c155]Matthew E. Taylor, Gregory Kuhlmann, Peter Stone:
Autonomous transfer for reinforcement learning. AAMAS (1) 2008: 283-290 - [c154]Nicholas K. Jong, Todd Hester, Peter Stone:
The utility of temporal abstraction in reinforcement learning. AAMAS (1) 2008: 299-306 - [c153]Kurt M. Dresner, Peter Stone:
Mitigating catastrophic failure at intersections of autonomous vehicles. AAMAS (3) 2008: 1393-1396 - [c152]Mark Van Middlesworth, Kurt M. Dresner, Peter Stone:
Replacing the stop sign: unmanaged intersection control for autonomous vehicles. AAMAS (3) 2008: 1413-1416 - [c151]Jonathan Wildstrom, Peter Stone, Emmett Witchel:
CARVE: A Cognitive Agent for Resource Value Estimation. ICAC 2008: 182-191 - [c150]Joseph Reisinger, Peter Stone, Risto Miikkulainen:
Online kernel selection for Bayesian reinforcement learning. ICML 2008: 816-823 - [c149]W. Bradley Knox, Juhyun Lee, Peter Stone:
Person recognition on a Segway Robot: A video of UT Austin Villa Robocup@Home 2007 finals demonstration. ICRA 2008: 1785-1786 - [c148]Daniel Stronger, Peter Stone:
Maximum likelihood estimation of sensor and action model functions on a mobile robot. ICRA 2008: 2104-2109 - [c147]Juhyun Lee, Peter Stone:
Person tracking on a mobile robot with heterogeneous inter-characteristic feedback. ICRA 2008: 2577-2582 - [c146]Todd Hester, Peter Stone:
Negative information and line observations for Monte Carlo localization. ICRA 2008: 2764-2769 - [c145]Doran Chakraborty, Peter Stone:
Online Multiagent Learning against Memory Bounded Adversaries. ECML/PKDD (1) 2008: 211-226 - [c144]Matthew E. Taylor, Nicholas K. Jong, Peter Stone:
Transferring Instances for Model-Based Reinforcement Learning. ECML/PKDD (2) 2008: 488-505 - [c143]