Stone, Peter

188 publications

CVPR 2025 Argus: A Compact and Versatile Foundation Model for Vision Weiming Zhuang, Chen Chen, Zhizhong Li, Sina Sajadmanesh, Jingtao Li, Jiabo Huang, Vikash Sehwag, Vivek Sharma, Hirotaka Shinozaki, Felan Carlo Garcia, Yihao Zhan, Naohiro Adachi, Ryoji Eki, Michael Spranger, Peter Stone, Lingjuan Lyu

CoRL 2025 ComposableNav: Instruction-Following Navigation in Dynamic Environments via Composable Diffusion Zichao Hu, Chen Tang, Michael Joseph Munje, Yifeng Zhu, Alex Liu, Shuijing Liu, Garrett Warnell, Peter Stone, Joydeep Biswas

AAAI 2025 Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes Chen Tang, Ben Abbatematteo, Jiaheng Hu, Rohan Chandra, Roberto Martín-Martín, Peter Stone

NeurIPS 2025 Dyn-O: Building Structured World Models with Object-Centric Representations Zizhao Wang, Kaixin Wang, Li Zhao, Peter Stone, Jiang Bian

NeurIPS 2025 Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia Chandler Smith, Marwa Abdulhai, Manfred Diaz, Marko Tesic, Rakshit Trivedi, Sasha Vezhnevets, Lewis Hammond, Jesse Clifton, Minsuk Chang, Edgar A. Duéñez-Guzmán, John P Agapiou, Jayd Matyas, Danny Karmon, Beining Zhang, Jim Dilkes, Akash Kundu, Jord Nguyen, Emanuel Tewolde, Jebish Purbey, Ram Mohan Rao Kadiyala, Siddhant Gupta, Aliaksei Korshuk, Buyantuev Alexander, Ilya Makarov, Gang Zhao, Rolando Fernandez, Zhihan Wang, Caroline Wang, Jiaxun Cui, Lingyun Xiao, Di Yang Shi, Yoonchang Sung, Arrasy Rahman, Peter Stone, Yipeng Kang, Hyeonggeun Yun, Ananya Ananya, Taehun Cha, Zhiqiang Wu, Elizaveta Tennant, Olivia Macmillan-Scott, Marta Emili García Segura, Diana Riazi, Fuyang Cui, Sriram Ganapathi Subramanian, Toryn Q. Klassen, Nico Schiavone, Mogtaba Alim, Sheila A. McIlraith, Manuel Sebastian Rios Beltran, Oswaldo Peña, Carlos Saith Rodriguez Rojas, Manuela Chacon-Chamorro, Ruben Manrique, Luis Felipe Giraldo, Nicanor Quijano, Yiding Wang, Yuxuan Chen, Fangwei Zhong, Mengmeng Wang, Wenming Tu, Zhaowei Zhang, Ziang Chen, Zixia Jia, Xue Feng, Zilong Zheng, Chichen Lin, Weijian Fan, Chenao Liu, Sneheel Sarangi, Ziyan Wang, Shuqing Shi, Yali Du, Avinaash Anand Kulandaivel, Yang Liu, Wu Ruiyang, Chetan Talele, 陆孙嘉, Gema Parreño Piqueras, Shamika Dhuri, Bain McHale, Tim Baarslag, Dylan Hadfield-Menell, Natasha Jaques, Jose Hernandez-Orallo, Joel Z Leibo

ICML 2025 Hyperspherical Normalization for Scalable Deep Reinforcement Learning Hojoon Lee, Youngdo Lee, Takuma Seno, Donghu Kim, Peter Stone, Jaegul Choo

ICLRW 2025 Learning Memory Mechanisms for Decision Making Through Demonstration William Yue, Bo Liu, Peter Stone

ICLR 2025 Learning a Fast Mixing Exogenous Block MDP Using a Single Trajectory Alexander Levine, Peter Stone, Amy Zhang

ICLR 2025 Longhorn: State Space Models Are Amortized Online Learners Bo Liu, Rui Wang, Lemeng Wu, Yihao Feng, Peter Stone, Qiang Liu

CoRL 2025 MEReQ: Max-Ent Residual-Q Inverse RL for Sample-Efficient Alignment from Intervention Yuxin Chen, Chen Tang, Jianglan Wei, Chenran Li, Thomas Tian, Xiang Zhang, Wei Zhan, Peter Stone, Masayoshi Tomizuka

ICML 2025 Proto Successor Measure: Representing the Behavior Space of an RL Agent Siddhant Agarwal, Harshit Sikchi, Peter Stone, Amy Zhang

ICLRW 2025 RL Zero: Zero-Shot Language to Behaviors Without Any Supervision Harshit Sikchi, Siddhant Agarwal, Pranaya Jajoo, Samyak Parajuli, Caleb Chuck, Max Rudolph, Peter Stone, Amy Zhang, Scott Niekum

NeurIPS 2025 RLZero: Direct Policy Inference from Language Without In-Domain Supervision Harshit Sikchi, Siddhant Agarwal, Pranaya Jajoo, Samyak Parajuli, Caleb Chuck, Max Rudolph, Peter Stone, Amy Zhang, Scott Niekum

CoRL 2025 SLAC: Simulation-Pretrained Latent Action Space for Whole-Body Real-World RL Jiaheng Hu, Peter Stone, Roberto Martín-Martín

ICLR 2025 SimBa: Simplicity Bias for Scaling up Parameters in Deep Reinforcement Learning Hojoon Lee, Dongyoon Hwang, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter R. Wurman, Jaegul Choo, Peter Stone, Takuma Seno

CoRL 2025 SocialNav-SUB: Benchmarking VLMs for Scene Understanding in Social Robot Navigation Michael Joseph Munje, Chen Tang, Shuijing Liu, Zichao Hu, Yifeng Zhu, Jiaxun Cui, Garrett Warnell, Joydeep Biswas, Peter Stone

AAAI 2025 The Essentials of AI for Life and Society: An AI Literacy Course for the University Community Joydeep Biswas, Don Fussell, Peter Stone, Kristin Patterson, Kristen Procko, Lea Sabatini, Zifan Xu

AAAI 2024 Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning Zizhao Wang, Caroline Wang, Xuesu Xiao, Yuke Zhu, Peter Stone

JMLR 2024 Data-Efficient Policy Evaluation Through Behavior Policy Search Josiah P. Hanna, Yash Chandak, Philip S. Thomas, Martha White, Peter Stone, Scott Niekum

NeurIPS 2024 Discovering Creative Behaviors Through DUPLEX: Diverse Universal Features for Policy Exploration Borja G. Leon, Francesco Riccio, Kaushik Subramanian, Peter R. Wurman, Peter Stone

NeurIPS 2024 Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning Jiaheng Hu, Zizhao Wang, Peter Stone, Roberto Martín-Martín

AAAI 2024 Learning Optimal Advantage from Preferences and Mistaking It for Reward W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum

CoRL 2024 Learning to Look: Seeking Information for Decision Making via Policy Factorization Shivin Dass, Jiaheng Hu, Ben Abbatematteo, Peter Stone, Roberto Martín-Martín

AAAI 2024 Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents Muhammad Rahman, Jiaxun Cui, Peter Stone

TMLR 2024 Models of Human Preference for Learning Reward Functions W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro G Allievi

NeurIPS 2024 N-Agent Ad Hoc Teamwork Caroline Wang, Arrasy Rahman, Ishan Durugkar, Elad Liebman, Peter Stone

AAAI 2024 Reward (Mis)design for Autonomous Driving (Abstract Reprint) W. Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone

ICLR 2024 Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks Ziping Xu, Zifan Xu, Runxuan Jiang, Peter Stone, Ambuj Tewari

NeurIPS 2024 SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone

CoLLAs 2024 T-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making William Yue, Bo Liu, Peter Stone

UAI 2023 Composing Efficient, Robust Tests for Policy Selection Dustin Morrill, Thomas J. Walsh, Daniel Hernandez, Peter R. Wurman, Peter Stone

AAAI 2023 DM²: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching Caroline Wang, Ishan Durugkar, Elad Liebman, Peter Stone

NeurIPS 2023 ELDEN: Exploration via Local Dependencies Zizhao Wang, Jiaheng Hu, Peter Stone, Roberto Martín-Martín

TMLR 2023 Event Tables for Efficient Experience Replay Varun Raj Kompella, Thomas Walsh, Samuel Barrett, Peter R. Wurman, Peter Stone

NeurIPS 2023 F-Policy Gradients: A General Framework for Goal-Conditioned RL Using F-Divergences Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang

NeurIPS 2023 FAMO: Fast Adaptive Multitask Optimization Bo Liu, Yihao Feng, Peter Stone, Qiang Liu

NeurIPS 2023 LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, Peter Stone

NeurIPSW 2023 Latent Skill Discovery for Chain-of-Thought Reasoning Zifan Xu, Haozhu Wang, Dmitriy Bespalov, Peter Stone, Yanjun Qi

CoRL 2023 Learning Generalizable Manipulation Policies with Object-Centric 3D Representations Yifeng Zhu, Zhenyu Jiang, Peter Stone, Yuke Zhu

ICMLW 2023 Learning Optimal Advantage from Preferences and Mistaking It for Reward W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, Serena Booth, Anca Dragan, Peter Stone, Scott Niekum

ICLR 2023 MACTA: A Multi-Agent Reinforcement Learning Approach for Cache Timing Attacks and Detection Jiaxun Cui, Xiaomeng Yang, Mulong Luo, Geunbae Lee, Peter Stone, Hsien-Hsin S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, Yuandong Tian

AAAI 2023 Metric Residual Network for Sample Efficient Goal-Conditioned Reinforcement Learning Bo Liu, Yihao Feng, Qiang Liu, Peter Stone

CoLLAs 2023 Model-Based Meta Automatic Curriculum Learning Zifan Xu, Yulin Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian Jiang, Bo Liu, Peter Stone

CoRL 2023 STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience Haresh Karnan, Elvin Yang, Daniel Farkash, Garrett Warnell, Joydeep Biswas, Peter Stone

NeurIPSW 2023 T-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making William Yue, Bo Liu, Peter Stone

AAAI 2023 The Perils of Trial-and-Error Reward Design: Misdesign Through Overfitting and Invalid Task Specifications Serena Booth, W. Bradley Knox, Julie Shah, Scott Niekum, Peter Stone, Alessandro Allievi

CoLLAs 2022 A Rule-Based Shield: Accumulating Safety Rules from Catastrophic Action Effects Shahaf S. Shperberg, Bo Liu, Alessandro Allievi, Peter Stone

NeurIPSW 2022 ABC: Adversarial Behavioral Cloning for Offline Mode-Seeking Imitation Learning Eddy Hudson, Ishan Durugkar, Garrett Warnell, Peter Stone

NeurIPS 2022 BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach Bo Liu, Mao Ye, Stephen Wright, Peter Stone, Qiang Liu

NeurIPSW 2022 BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach Mao Ye, Bo Liu, Stephen Wright, Peter Stone, Qiang Liu

ICML 2022 Causal Dynamics Learning for Task-Independent State Abstraction Zizhao Wang, Xuesu Xiao, Zifan Xu, Yuke Zhu, Peter Stone

CoLLAs 2022 Continual Learning and Private Unlearning Bo Liu, Qiang Liu, Peter Stone

CVPR 2022 Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles Jiaxun Cui, Hang Qiu, Dian Chen, Peter Stone, Yuke Zhu

IJCAI 2022 Dynamic Sparse Training for Deep Reinforcement Learning Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone

CoRL 2022 Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning Yoonchang Sung, Zizhao Wang, Peter Stone

ICMLW 2022 Model-Based Meta Automatic Curriculum Learning Zifan Xu, Yulin Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian Jiang, Bo Liu, Peter Stone

ICMLW 2022 Task Factorization in Curriculum Learning Reuth Mirsky, Shahaf S. Shperberg, Yulin Zhang, Zifan Xu, Yuqian Jiang, Jiaxun Cui, Peter Stone

CoRL 2022 VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors Yifeng Zhu, Abhishek Joshi, Peter Stone, Yuke Zhu

NeurIPS 2022 Value Function Decomposition for Iterative Design of Reinforcement Learning Agents James MacGlashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan, Peter Wurman, Peter Stone

NeurIPS 2021 Adversarial Intrinsic Motivation for Reinforcement Learning Ishan Durugkar, Mauricio Tec, Scott Niekum, Peter Stone

JAIR 2021 Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies Roberto Capobianco, Varun Raj Kompella, James Ault, Guni Sharon, Stacy Jong, Spencer J. Fox, Lauren Ancel Meyers, Peter R. Wurman, Peter Stone

ICML 2021 Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar

NeurIPS 2021 Conflict-Averse Gradient Descent for Multi-Task Learning Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, Qiang Liu

AAAI 2021 Demonstration of the EMPATHIC Framework for Task Learning from Implicit Human Feedback Yuchen Cui, Qiping Zhang, Sahil Jain, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox

AAAI 2021 Expected Value of Communication for Planning in Ad Hoc Teamwork William Macke, Reuth Mirsky, Peter Stone

AAAI 2021 Goal Blending for Responsive Shared Autonomy in a Navigating Vehicle Yu-Sian Jiang, Garrett Warnell, Peter Stone

MLJ 2021 Grounded Action Transformation for Sim-to-Real Reinforcement Learning Josiah P. Hanna, Siddharth Desai, Haresh Karnan, Garrett Warnell, Peter Stone

MLJ 2021 Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy Josiah P. Hanna, Scott Niekum, Peter Stone

NeurIPS 2021 Machine Versus Human Attention in Deep Reinforcement Learning Tasks Suna Guo, Ruohan Zhang, Bo Liu, Yifeng Zhu, Dana Ballard, Mary M. Hayhoe, Peter Stone

AAAI 2021 Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks Yuqian Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, Peter Stone

IJCAI 2020 A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork Reuth Mirsky, William Macke, Andy Wang, Harel Yedidsion, Peter Stone

NeurIPS 2020 An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone

IJCAI 2020 Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning Ishan Durugkar, Elad Liebman, Peter Stone

JMLR 2020 Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, Peter Stone

NeurIPS 2020 Firefly Neural Architecture Descent: A General Approach for Growing Neural Networks Lemeng Wu, Bo Liu, Peter Stone, Qiang Liu

ICMLW 2020 Generalizing Curricula for Reinforcement Learning Sanmit Narvekar, Peter Stone

JAIR 2020 Jointly Improving Parsing and Perception for Natural Language Commands Through Human-Robot Dialog Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin W. Hart, Peter Stone, Raymond J. Mooney

CoRL 2020 Learning to Improve Multi-Robot Hallway Navigation Jin Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, Peter Stone

ICML 2020 Reducing Sampling Error in Batch Temporal Difference Learning Brahma Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone

CoRL 2020 The EMPATHIC Framework for Task Learning from Implicit Human Feedback Yuchen Cui, Qiping Zhang, Brad Knox, Alessandro Allievi, Peter Stone, Scott Niekum

JAIR 2020 The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation Shih-Yun Lo, Shiqi Zhang, Peter Stone

IJCAI 2019 Ad Hoc Teamwork with Behavior Switching Agents Manish Ravula, Shani Alkoby, Peter Stone

IJCAI 2019 Imitation Learning from Video by Leveraging Proprioception Faraz Torabi, Garrett Warnell, Peter Stone

ICML 2019 Importance Sampling Policy Evaluation with an Estimated Behavior Policy Josiah Hanna, Scott Niekum, Peter Stone

IJCAI 2019 Leveraging Human Guidance for Deep Reinforcement Learning Tasks Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, Peter Stone

IJCAI 2019 Recent Advances in Imitation Learning from Observation Faraz Torabi, Garrett Warnell, Peter Stone

AAAI 2019 Selecting Compliant Agents for Opt-in Micro-Tolling Josiah P. Hanna, Guni Sharon, Stephen D. Boyles, Peter Stone

AAAI 2018 Adversarial Goal Generation for Intrinsic Motivation Ishan Durugkar, Peter Stone

IJCAI 2018 Behavioral Cloning from Observation Faraz Torabi, Garrett Warnell, Peter Stone

AAAI 2018 Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces Garrett Warnell, Nicholas R. Waytowich, Vernon Lawhern, Peter Stone

AAAI 2018 DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation Haipeng Chen, Bo An, Guni Sharon, Josiah P. Hanna, Peter Stone, Chunyan Miao, Yeng Chai Soh

AAAI 2018 Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions Jesse Thomason, Jivko Sinapov, Raymond J. Mooney, Peter Stone

IJCAI 2018 Multi-Modal Predicate Identification Using Dynamically Learned Robot Controllers Saeid Amiri, Suhua Wei, Shiqi Zhang, Jivko Sinapov, Jesse Thomason, Peter Stone

AAAI 2018 Traffic Optimization for a Mixture of Self-Interested and Compliant Agents Guni Sharon, Michael Albert, Tarun Rambha, Stephen D. Boyles, Peter Stone

AAAI 2017 Automated Design of Robust Mechanisms Michael Albert, Vincent Conitzer, Peter Stone

AAAI 2017 Automatic Curriculum Graph Generation for Reinforcement Learning Agents Maxwell Svetlik, Matteo Leonetti, Jivko Sinapov, Rishi Shah, Nick Walker, Peter Stone

IJCAI 2017 Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning Sanmit Narvekar, Jivko Sinapov, Peter Stone

AAAI 2017 Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation Josiah P. Hanna, Peter Stone, Scott Niekum

ICML 2017 Data-Efficient Policy Evaluation Through Behavior Policy Search Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum

AAAI 2017 Designing Better Playlists with Monte Carlo Tree Search Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, Peter Stone

AAAI 2017 Dynamically Constructed (PO)MDPs for Adaptive Robot Planning Shiqi Zhang, Piyush Khandelwal, Peter Stone

AAAI 2017 Grounded Action Transformation for Robot Learning in Simulation Josiah P. Hanna, Peter Stone

CoRL 2017 Opportunistic Active Learning for Grounding Natural Language Descriptions Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Justin W. Hart, Peter Stone, Raymond J. Mooney

AAAI 2016 Autonomous Electricity Trading Using Time-of-Use Tariffs in a Competitive Market Daniel Urieli, Peter Stone

ICLR 2016 Deep Reinforcement Learning in Parameterized Action Space Matthew J. Hausknecht, Peter Stone

IJCAI 2016 Learning Multi-Modal Grounded Linguistic Semantics by Playing "i Spy" Jesse Thomason, Jivko Sinapov, Maxwell Svetlik, Peter Stone, Raymond J. Mooney

IJCAI 2016 Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors Jivko Sinapov, Priyanka Khante, Maxwell Svetlik, Peter Stone

ICML 2016 On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search Piyush Khandelwal, Elad Liebman, Scott Niekum, Peter Stone

IJCAI 2016 Robot Scavenger Hunt: A Standardized Framework for Evaluating Intelligent Mobile Robots Shiqi Zhang, Dongcai Lu, Xiaoping Chen, Peter Stone

AAAI 2016 What's Hot at RoboCup Peter Stone

AAAI 2015 CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied to Dialog with a Mobile Robot Shiqi Zhang, Peter Stone

AAAI 2015 Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork Samuel Barrett, Peter Stone

IJCAI 2015 Learning to Interpret Natural Language Commands Through Human-Robot Dialog Jesse Thomason, Shiqi Zhang, Raymond J. Mooney, Peter Stone

AAAI 2015 Placing Influencing Agents in a Flock Katie Genter, Peter Stone

AAAI 2015 SCRAM: Scalable Collision-Avoiding Role Assignment with Minimal-Makespan for Formational Positioning Patrick MacAlpine, Eric Price, Peter Stone

AAAI 2015 UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning Patrick MacAlpine, Mike Depinet, Peter Stone

IJCAI 2015 When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing Fei Fang, Peter Stone, Milind Tambe

AAAI 2014 Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27 -31, 2014, Québec City, Québec, Canada Carla E. Brodley, Peter Stone

AAAI 2014 TacTex'13: A Champion Adaptive Power Trading Agent Daniel Urieli, Peter Stone

ECML-PKDD 2013 Model-Selection for Non-Parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System Daniel Urieli, Peter Stone

MLJ 2013 TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots Todd Hester, Peter Stone

AAAI 2013 Teamwork with Limited Knowledge of Teammates Samuel Barrett, Peter Stone, Sarit Kraus, Avi Rosenfeld

AAAI 2012 Design and Optimization of an Omnidirectional Humanoid Walk: A Winning Approach at the RoboCup 2011 3D Simulation Competition Patrick MacAlpine, Samuel Barrett, Daniel Urieli, Victor Vu, Peter Stone

ICML 2012 PAC Subset Selection in Stochastic Multi-Armed Bandits Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, Peter Stone

AAAI 2011 Ad Hoc Teamwork in Variations of the Pursuit Domain Samuel Barrett, Peter Stone

MLJ 2011 Characterizing Reinforcement Learning Methods Through Parameterized Learning Problems Shivaram Kalyanakrishnan, Peter Stone

AAAI 2011 Comparing Agents' Success Against People in Security Domains Raz Lin, Sarit Kraus, Noa Agmon, Samuel Barrett, Peter Stone

AAAI 2011 Enforcing Liveness in Autonomous Traffic Management Tsz-Chiu Au, Neda Shahidi, Peter Stone

AAAI 2011 Multiagent Patrol Generalized to Complex Environmental Conditions Noa Agmon, Daniel Urieli, Peter Stone

AAAI 2011 Role-Based Ad Hoc Teamwork Katie Long Genter, Noa Agmon, Peter Stone

ICML 2011 Structure Learning in Ergodic Factored MDPs Without Knowledge of the Transition Function's In-Degree Doran Chakraborty, Peter Stone

AAAI 2010 Ad Hoc Autonomous Agent Teams: Collaboration Without Pre-Coordination Peter Stone, Gal A. Kaminka, Sarit Kraus, Jeffrey S. Rosenschein

ICML 2010 Boosting for Regression Transfer David Pardoe, Peter Stone

ICML 2010 Convergence, Targeted Optimality, and Safety in Multiagent Learning Doran Chakraborty, Peter Stone

ICML 2010 Efficient Selection of Multiple Bandit Arms: Theory and Practice Shivaram Kalyanakrishnan, Peter Stone

ECML-PKDD 2010 Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-like Exploration Tobias Jung, Peter Stone

ECML-PKDD 2009 Compositional Models for Reinforcement Learning Nicholas K. Jong, Peter Stone

ECML-PKDD 2009 Feature Selection for Value Function Approximation Using Bayesian Model Selection Tobias Jung, Peter Stone

JMLR 2009 Transfer Learning for Reinforcement Learning Domains: A Survey Matthew E. Taylor, Peter Stone

JAIR 2008 A Multiagent Approach to Autonomous Intersection Management Kurt M. Dresner, Peter Stone

ICML 2008 Online Kernel Selection for Bayesian Reinforcement Learning Joseph Reisinger, Peter Stone, Risto Miikkulainen

ECML-PKDD 2008 Online Multiagent Learning Against Memory Bounded Adversaries Doran Chakraborty, Peter Stone

ECML-PKDD 2008 Transferring Instances for Model-Based Reinforcement Learning Matthew E. Taylor, Nicholas K. Jong, Peter Stone

IJCAI 2007 Color Learning on a Mobile Robot: Towards Full Autonomy Under Changing Illumination Mohan Sridharan, Peter Stone

ICML 2007 Cross-Domain Transfer for Reinforcement Learning Matthew E. Taylor, Peter Stone

IJCAI 2007 General Game Learning Using Knowledge Transfer Bikramjit Banerjee, Peter Stone

IJCAI 2007 Learning and Multiagent Reasoning for Autonomous Agents Peter Stone

IJCAI 2007 Machine Learning for On-Line Hardware Reconfiguration Jonathan Wildstrom, Peter Stone, Emmett Witchel, Michael Dahlin

AAAI 2007 Representation Transfer via Elaboration Matthew E. Taylor, Peter Stone

IJCAI 2007 Sharing the Road: Autonomous Vehicles Meet Human Drivers Kurt M. Dresner, Peter Stone

AAAI 2007 Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison Matthew E. Taylor, Shimon Whiteson, Peter Stone

JMLR 2007 Transfer Learning via Inter-Task Mappings for Temporal Difference Learning Matthew E. Taylor, Peter Stone, Yaxin Liu

AAAI 2006 Automatic Heuristic Construction for General Game Playing Gregory Kuhlmann, Peter Stone

AAAI 2006 Automatic Heuristic Construction in a Complete General Game Player Gregory Kuhlmann, Peter Stone

AAAI 2006 Biconnected Structure for Multi-Robot Systems Mazda Ahmadi, Peter Stone

JMLR 2006 Evolutionary Function Approximation for Reinforcement Learning Shimon Whiteson, Peter Stone

AAAI 2006 Expectation-Based Vision for Self-Localization on a Legged Robot Daniel Stronger, Peter Stone

AAAI 2006 Inter-Task Action Correlation for Reinforcement Learning Tasks Matthew E. Taylor, Peter Stone

AAAI 2006 Keeping in Touch: Maintaining Biconnected Structure by Homogeneous Robots Mazda Ahmadi, Peter Stone

AAAI 2006 Know Thine Enemy: A Champion RoboCup Coach Agent Gregory Kuhlmann, William B. Knox, Peter Stone

AAAI 2006 Making Autonomous Intersection Management Backwards-Compatible Kurt M. Dresner, Peter Stone

AAAI 2006 Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning Shimon Whiteson, Peter Stone

AAAI 2006 TacTex-05: A Champion Supply Chain Management Agent David Pardoe, Peter Stone

AAAI 2006 Traffic Intersections of the Future Kurt M. Dresner, Peter Stone

AAAI 2006 Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping Yaxin Liu, Peter Stone

AAAI 2005 Autonomous Color Learning on a Mobile Robot Mohan Sridharan, Peter Stone

MLJ 2005 Evolving Soccer Keepaway Players Through Task Decomposition Shimon Whiteson, Nate Kohl, Risto Miikkulainen, Peter Stone

AAAI 2005 Improving Action Selection in MDP's via Knowledge Transfer Alexander A. Sherstov, Peter Stone

IJCAI 2005 State Abstraction Discovery from Irrelevant State Variables Nicholas K. Jong, Peter Stone

AAAI 2005 Value Functions for RL-Based Behavior Transfer: A Comparative Study Matthew E. Taylor, Peter Stone, Yaxin Liu

AAAI 2004 Machine Learning for Fast Quadrupedal Locomotion Nate Kohl, Peter Stone

AAAI 2004 Towards Autonomic Computing: Adaptive Job Routing and Scheduling Shimon Whiteson, Peter Stone

JAIR 2003 Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions Peter Stone, Robert E. Schapire, Michael L. Littman, János A. Csirik, David A. McAllester

ICML 2003 Learning Predictive State Representations Satinder Singh, Michael L. Littman, Nicholas K. Jong, David Pardoe, Peter Stone

ICML 2002 Modeling Auction Price Uncertainty Using Boosting-Based Conditional Density Estimation Robert E. Schapire, Peter Stone, David A. McAllester, Michael L. Littman, János A. Csirik

AAAI 2002 The 2001 Trading Agent Competition Michael P. Wellman, Amy Greenwald, Peter Stone, Peter R. Wurman

JAIR 2001 ATTac-2000: An Adaptive Autonomous Bidding Agent Peter Stone, Michael L. Littman, Satinder Singh, Michael J. Kearns

ICML 2001 Scaling Reinforcement Learning Toward RoboCup Soccer Peter Stone, Richard S. Sutton

AAAI 2000 Cobot in LambdaMOO: A Social Statistics Agent Charles Lee Isbell Jr., Michael J. Kearns, David P. Kormann, Satinder Singh, Peter Stone

AAAI 2000 Defining and Using Ideal Teammate and Opponent Agent Models Peter Stone, Patrick Riley, Manuela M. Veloso

ECML-PKDD 2000 Layered Learning Peter Stone, Manuela M. Veloso

ICML 2000 TPOT-RL Applied to Network Routing Peter Stone

AAAI 1999 CMUnited-98: A Team of Robotic Soccer Agents Manuela M. Veloso, Michael H. Bowling, Sorin Achim, Kwun Han, Peter Stone

AAAI 1997 Layered Learning in Multiagent Systems Peter Stone

IJCAI 1997 The RoboCup Synthetic Agent Challenge 97 Hiroaki Kitano, Milind Tambe, Peter Stone, Manuela M. Veloso, Silvia Coradeschi, Eiichi Osawa, Hitoshi Matsubara, Itsuki Noda, Minoru Asada

NeurIPS 1995 Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function Peter Stone, Manuela M. Veloso

JAIR 1995 FLECS: Planning with a Flexible Commitment Strategy Manuela M. Veloso, Peter Stone