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- affiliation: University of Texas at Austin, USA
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2020 – today
- 2023
[j114]W. Bradley Knox
, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone:
Reward (Mis)design for autonomous driving. Artif. Intell. 316: 103829 (2023)- [j113]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) - [j112]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 L. 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) - [c448]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 - [c447]Bo Liu, Yihao Feng, Qiang Liu, Peter Stone:
Metric Residual Network for Sample Efficient Goal-Conditioned Reinforcement Learning. AAAI 2023: 8799-8806 - [c446]Caroline Wang, Ishan Durugkar, Elad Liebman, Peter Stone:
DM²: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching. AAAI 2023: 11699-11707 - [c445]Vaibhav Bajaj, Guni Sharon, Peter Stone:
Task Phasing: Automated Curriculum Learning from Demonstrations. ICAPS 2023: 542-550 - [c444]Caroline Wang, Garrett Warnell, Peter Stone:
D-Shape: Demonstration-Shaped Reinforcement Learning via Goal-Conditioning. AAMAS 2023: 1267-1275 - [c443]Shahaf S. Shperberg, Bo Liu, Peter Stone:
Relaxed Exploration Constrained Reinforcement Learning. AAMAS 2023: 2821-2823 - [c442]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 - [c441]Zifan Xu, Bo Liu, Xuesu Xiao, Anirudh Nair, Peter Stone:
Benchmarking Reinforcement Learning Techniques for Autonomous Navigation. ICRA 2023: 9224-9230 - [c440]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 - [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 - [i133]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 L. 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) - [i132]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) - [i131]Jiaheng Hu, Peter Stone, Roberto Martín-Martín:
Causal Policy Gradient for Whole-Body Mobile Manipulation. CoRR abs/2305.04866 (2023) - [i130]Yoonchang Sung, Peter Stone:
Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search. CoRR abs/2305.10395 (2023) - [i129]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) - [i128]Bo Liu, Yihao Feng, Peter Stone, Qiang Liu:
FAMO: Fast Adaptive Multitask Optimization. CoRR abs/2306.03792 (2023) - [i127]Dustin Morrill, Thomas J. Walsh, Daniel Hernandez, Peter R. Wurman, Peter Stone:
Composing Efficient, Robust Tests for Policy Selection. CoRR abs/2306.07372 (2023) - [i126]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) - [i125]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) - [i124]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) - [i123]Arrasy Rahman, Jiaxun Cui, Peter Stone:
Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents. CoRR abs/2308.09595 (2023) - [i122]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) - [i121]Elad Liebman, Peter Stone:
Utilizing Mood-Inducing Background Music in Human-Robot Interaction. CoRR abs/2308.14269 (2023) - [i120]Yoonchang Sung, Rahul Shome, Peter Stone:
Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning. CoRR abs/2309.08897 (2023) - [i119]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) - [i118]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) - 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 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) - [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 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
- [j102]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) - [j101]Roberto Capobianco, Varun 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) - [j100]Josiah P. Hanna, Scott Niekum, Peter Stone:
Importance sampling in reinforcement learning with an estimated behavior policy. Mach. Learn. 110(6): 1267-1317 (2021) - [j99]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) - [j98]Bo Liu, Xuesu Xiao, Peter Stone:
A Lifelong Learning Approach to Mobile Robot Navigation. IEEE Robotics Autom. Lett. 6(2): 1090-1096 (2021) - [j97]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) - [j96]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) - [j95]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) - [j94]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) - [j93]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 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]