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- affiliation: University of Texas at Austin, USA
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2020 – today
- 2023
[j113]W. Bradley Knox
, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone:
Reward (Mis)design for autonomous driving. Artif. Intell. 316: 103829 (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) - [c437]Caroline Wang, Garrett Warnell, Peter Stone:
D-Shape: Demonstration-Shaped Reinforcement Learning via Goal-Conditioning. AAMAS 2023: 1267-1275 - [c436]Shahaf S. Shperberg, Bo Liu, Peter Stone:
Relaxed Exploration Constrained Reinforcement Learning. AAMAS 2023: 2821-2823 - [i121]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) - [i120]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) - [i119]Jiaheng Hu, Peter Stone, Roberto Martín-Martín:
Causal Policy Gradient for Whole-Body Mobile Manipulation. CoRR abs/2305.04866 (2023) - [i118]Yoonchang Sung, Peter Stone:
Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search. CoRR abs/2305.10395 (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]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,