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- affiliation: University of Texas at Austin, USA
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2020 – today
- 2024
[j123]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 Roscon, 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)- [j122]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) - [j121]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) - [j120]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) - [j119]Shiqi Zhang, Piyush Khandelwal, Peter Stone:
iCORPP: Interleaved commonsense reasoning and probabilistic planning on robots. Robotics Auton. Syst. 174: 104613 (2024) - [j118]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) - [j117]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) - [c470]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 - [c469]Zizhao Wang, Caroline Wang, Xuesu Xiao, Yuke Zhu, Peter Stone:
Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning. AAAI 2024: 15778-15786 - [c468]Muhammad Rahman, Jiaxun Cui, Peter Stone:
Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents. AAAI 2024: 17523-17530 - [c467]W. Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone:
Reward (Mis)design for Autonomous Driving (Abstract Reprint). AAAI 2024: 22702 - [c466]Shahaf S. Shperberg, Bo Liu, Peter Stone:
Relaxed Exploration Constrained Reinforcement Learning. AAMAS 2024: 1727-1735 - [c465]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 - [c464]Ziping Xu, Zifan Xu, Runxuan Jiang, Peter Stone, Ambuj Tewari:
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks. ICLR 2024 - [c463]Zifan Xu, Amir Hossain Raj, Xuesu Xiao, Peter Stone:
Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning. ICRA 2024: 11474-11480 - [c462]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 - [c461]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 - [c460]Yoonchang Sung, Rahul Shome, Peter Stone:
Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning. ICRA 2024: 17086-17092 - [i160]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) - [i159]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) - [i158]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) - [i157]Zifan Xu, Amir Hossain Raj, Xuesu Xiao, Peter Stone:
Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning. CoRR abs/2403.03848 (2024) - [i156]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) - [i155]Alexander Levine, Peter Stone, Amy Zhang:
Multistep Inverse Is Not All You Need. CoRR abs/2403.11940 (2024) - [i154]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) - [i153]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) - [i152]Caroline Wang, Arrasy Rahman, Ishan Durugkar, Elad Liebman, Peter Stone:
N-Agent Ad Hoc Teamwork. CoRR abs/2404.10740 (2024) - [i151]Rolando Fernandez, Garrett Warnell, Derrik E. Asher, Peter Stone:
Multi-Agent Synchronization Tasks. CoRR abs/2404.18798 (2024) - [i150]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) - [i149]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) - [i148]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) - [i147]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) - [i146]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) - [i145]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) - [i144]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) - [i143]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) - 2023
- [j116]W. Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone:
Reward (Mis)design for autonomous driving. Artif. Intell. 316: 103829 (2023) - [j115]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) - [j114]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) - [j113]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) - [j112]Varun Raj Kompella, Thomas Walsh, Samuel Barrett, Peter R. Wurman, Peter Stone:
Event Tables for Efficient Experience Replay. Trans. Mach. Learn. Res. 2023 (2023) - [c459]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 - [c458]Bo Liu, Yihao Feng, Qiang Liu, Peter Stone:
Metric Residual Network for Sample Efficient Goal-Conditioned Reinforcement Learning. AAAI 2023: 8799-8806 - [c457]Caroline Wang, Ishan Durugkar, Elad Liebman, Peter Stone:
DM²: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching. AAAI 2023: 11699-11707 - [c456]Vaibhav Bajaj, Guni Sharon, Peter Stone:
Task Phasing: Automated Curriculum Learning from Demonstrations. ICAPS 2023: 542-550 - [c455]Caroline Wang, Garrett Warnell, Peter Stone:
D-Shape: Demonstration-Shaped Reinforcement Learning via Goal-Conditioning. AAMAS 2023: 1267-1275 - [c454]Shahaf S. Shperberg, Bo Liu, Peter Stone:
Relaxed Exploration Constrained Reinforcement Learning. AAMAS 2023: 2821-2823 - [c453]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 - [c452]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 - [c451]Yifeng Zhu, Zhenyu Jiang, Peter Stone, Yuke Zhu:
Learning Generalizable Manipulation Policies with Object-Centric 3D Representations. CoRL 2023: 3418-3433 - [c450]Swathi Mannem, William Macke, Peter Stone, Reuth Mirsky:
Exploring the Cost of Interruptions in Human-Robot Teaming. Humanoids 2023: 1-8 - [c449]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 - [c448]Zifan Xu, Bo Liu, Xuesu Xiao, Anirudh Nair, Peter Stone:
Benchmarking Reinforcement Learning Techniques for Autonomous Navigation. ICRA 2023: 9224-9230 - [c447]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 - [c446]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 - [c445]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 - [c444]Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang:
f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences. NeurIPS 2023 - [c443]Bo Liu, Yihao Feng, Peter Stone, Qiang Liu:
FAMO: Fast Adaptive Multitask Optimization. NeurIPS 2023 - [c442]Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, Peter Stone:
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning. NeurIPS 2023 - [c441]Zizhao Wang, Jiaheng Hu, Peter Stone, Roberto Martín-Martín:
ELDEN: Exploration via Local Dependencies. NeurIPS 2023 - [c440]Jiaheng Hu, Peter Stone, Roberto Martín-Martín:
Causal Policy Gradient for Whole-Body Mobile Manipulation. Robotics: Science and Systems 2023 - [c439]Yoonchang Sung, Peter Stone:
Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search. Robotics: Science and Systems 2023 - [c438]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 - [c437]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
- [j111]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) - [j110]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) - [j109]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) - [j108]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) - [j107]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) - [j106]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) - [j105]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) - [j104]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) - [j103]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) - [c436]Shahaf S. Shperberg, Bo Liu, Alessandro Allievi, Peter Stone:
A Rule-based Shield: Accumulating Safety Rules from Catastrophic Action Effects. CoLLAs 2022: 231-242 - [c435]Bo Liu, Qiang Liu, Peter Stone:
Continual Learning and Private Unlearning. CoLLAs 2022: 243-254 - [c434]Yifeng Zhu, Abhishek Joshi, Peter Stone, Yuke Zhu:
VIOLA: Object-Centric Imitation Learning for Vision-Based Robot Manipulation. CoRL 2022: 1199-1210 - [c433]Yoonchang Sung, Zizhao Wang, Peter Stone:
Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning. CoRL 2022: 2115-2124 - [c432]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 - [c431]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 - [c430]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 - [c429]Akarsh Kumar, Bo Liu, Risto Miikkulainen, Peter Stone:
Effective mutation rate adaptation through group elite selection. GECCO