Shimon Whiteson

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 215

Top Venues

CoRR

ICML

NeurIPS

AAMAS

Publications

Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert T. Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob N. Foerster
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. AAMAS (2024)
Alexander David Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob Nicolaus Foerster
Can Learned Optimization Make Reinforcement Learning Less Difficult? CoRR (2024)
Zheng Xiong, Risto Vuorio, Jacob Beck, Matthieu Zimmer, Kun Shao, Shimon Whiteson
Distilling Morphology-Conditioned Hypernetworks for Efficient Universal Morphology Control. CoRR (2024)
Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster
Discovering Temporally-Aware Reinforcement Learning Algorithms. ICLR (2024)
Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster
Discovering Temporally-Aware Reinforcement Learning Algorithms. CoRR (2024)
Reza Mahjourian, Rongbing Mu, Valerii Likhosherstov, Paul Mougin, Xiukun Huang, João V. Messias, Shimon Whiteson
UniGen: Unified Modeling of Initial Agent States and Trajectories for Generating Autonomous Driving Scenarios. ICRA (2024)
Risto Vuorio, Mattie Fellows, Cong Lu, Clémence Grislain, Shimon Whiteson
A Bayesian Solution To The Imitation Gap. CoRR (2024)
Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Zheng Xiong, Shimon Whiteson
SplAgger: Split Aggregation for Meta-Reinforcement Learning. CoRR (2024)
Matthew Thomas Jackson, Michael T. Matthews, Cong Lu, Benjamin Ellis, Shimon Whiteson, Jakob N. Foerster
Policy-Guided Diffusion. CoRR (2024)
Reza Mahjourian, Rongbing Mu, Valerii Likhosherstov, Paul Mougin, Xiukun Huang, João V. Messias, Shimon Whiteson
UniGen: Unified Modeling of Initial Agent States and Trajectories for Generating Autonomous Driving Scenarios. CoRR (2024)
Zheng Xiong, Jacob Beck, Shimon Whiteson
Universal Morphology Control via Contextual Modulation. CoRR (2023)
Jacob Beck, Risto Vuorio, Zheng Xiong, Shimon Whiteson
Recurrent Hypernetworks are Surprisingly Strong in Meta-RL. CoRR (2023)
Mattie Fellows, Matthew J. A. Smith, Shimon Whiteson
Why Target Networks Stabilise Temporal Difference Methods. ICML (2023)
Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. NeurIPS (2023)
Mingfei Sun, Sam Devlin, Jacob Beck, Katja Hofmann, Shimon Whiteson
Trust Region Bounds for Decentralized PPO Under Non-stationarity. AAMAS (2023)
Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa M. Zintgraf, Chelsea Finn, Shimon Whiteson
A Survey of Meta-Reinforcement Learning. CoRR (2023)
Benjamin Ellis, Jonathan Cook, Skander Moalla, Mikayel Samvelyan, Mingfei Sun, Anuj Mahajan, Jakob N. Foerster, Shimon Whiteson
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning. NeurIPS (2023)
Mattie Fellows, Brandon Kaplowitz, Christian Schröder de Witt, Shimon Whiteson
Bayesian Exploration Networks. CoRR (2023)
Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nick Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Yang, Shimon Whiteson, Brandyn White, Dragomir Anguelov
The Waymo Open Sim Agents Challenge. CoRR (2023)
Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob Nicolaus Foerster
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. CoRR (2023)
Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nicholas Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Yang, Shimon Whiteson, Brandyn White, Dragomir Anguelov
The Waymo Open Sim Agents Challenge. NeurIPS (2023)
Mattie Fellows, Matthew J. A. Smith, Shimon Whiteson
Why Target Networks Stabilise Temporal Difference Methods. CoRR (2023)
Maximilian Igl, Punit Shah, Paul Mougin, Sirish Srinivasan, Tarun Gupta, Brandyn White, Kyriacos Shiarlis, Shimon Whiteson
Hierarchical Imitation Learning for Stochastic Environments. IROS (2023)
Yat Long Lo, Christian Schröder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson
Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning. ICLR (2023)
Zheng Xiong, Jacob Beck, Shimon Whiteson
Universal Morphology Control via Contextual Modulation. ICML (2023)
Maximilian Igl, Punit Shah, Paul Mougin, Sirish Srinivasan, Tarun Gupta, Brandyn White, Kyriacos Shiarlis, Shimon Whiteson
Hierarchical Imitation Learning for Stochastic Environments. CoRR (2023)
Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Tjarko Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Nicolaus Foerster
JaxMARL: Multi-Agent RL Environments in JAX. CoRR (2023)
Mingfei Sun, Benjamin Ellis, Anuj Mahajan, Sam Devlin, Katja Hofmann, Shimon Whiteson
Trust-Region-Free Policy Optimization for Stochastic Policies. CoRR (2023)
Yat Long Lo, Christian Schröder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson
Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning. CoRR (2023)
Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, Sergey Levine
Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. IROS (2023)
Jacob Beck, Risto Vuorio, Zheng Xiong, Shimon Whiteson
Recurrent Hypernetworks are Surprisingly Strong in Meta-RL. NeurIPS (2023)
Matthew J. A. Smith, Jelena Luketina, Kristian Hartikainen, Maximilian Igl, Shimon Whiteson
Learning Skills Diverse in Value-Relevant Features. CoLLAs (2022)
Shangtong Zhang, Shimon Whiteson
Truncated Emphatic Temporal Difference Methods for Prediction and Control. J. Mach. Learn. Res. 23 (2022)
Samuel Sokota, Christian A. Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Martin Strohmeier, J. Zico Kolter, Shimon Whiteson, Jakob N. Foerster
Communicating via Markov Decision Processes. ICML (2022)
Eli Bronstein, Sirish Srinivasan, Supratik Paul, Aman Sinha, Matthew O'Kelly, Payam Nikdel, Shimon Whiteson
Embedding Synthetic Off-Policy Experience for Autonomous Driving via Zero-Shot Curricula. CoRR (2022)
Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
Monotonic Improvement Guarantees under Non-stationarity for Decentralized PPO. CoRR (2022)
Darius Muglich, Luisa M. Zintgraf, Christian Schröder de Witt, Shimon Whiteson, Jakob N. Foerster
Generalized Beliefs for Cooperative AI. CoRR (2022)
Darius Muglich, Christian Schröder de Witt, Elise van der Pol, Shimon Whiteson, Jakob N. Foerster
Equivariant Networks for Zero-Shot Coordination. NeurIPS (2022)
Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, M. Pawan Kumar
In Defense of the Unitary Scalarization for Deep Multi-Task Learning. CoRR (2022)
Darius Muglich, Luisa M. Zintgraf, Christian A. Schröder de Witt, Shimon Whiteson, Jakob N. Foerster
Generalized Beliefs for Cooperative AI. ICML (2022)
Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency. AAAI (2022)
Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin, Punit Shah, Kyriacos Shiarlis, Dragomir Anguelov, Mark Palatucci, Brandyn White, Shimon Whiteson
Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation. CoRR (2022)
Darius Muglich, Christian Schröder de Witt, Elise van der Pol, Shimon Whiteson, Jakob N. Foerster
Equivariant Networks for Zero-Shot Coordination. CoRR (2022)
Eli Bronstein, Mark Palatucci, Dominik Notz, Brandyn White, Alex Kuefler, Yiren Lu, Supratik Paul, Payam Nikdel, Paul Mougin, Hongge Chen, Justin Fu, Austin Abrams, Punit Shah, Evan Racah, Benjamin Frenkel, Shimon Whiteson, Dragomir Anguelov
Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. CoRR (2022)
Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin, Punit Shah, Kyriacos Shiarlis, Dragomir Anguelov, Mark Palatucci, Brandyn White, Shimon Whiteson
Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation. ICRA (2022)
Mingfei Sun, Vitaly Kurin, Guoqing Liu, Sam Devlin, Tao Qin, Katja Hofmann, Shimon Whiteson
You May Not Need Ratio Clipping in PPO. CoRR (2022)
Shangtong Zhang, Romain Laroche, Harm van Seijen, Shimon Whiteson, Remi Tachet des Combes
A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms. AAMAS (2022)
Benjamin Ellis, Skander Moalla, Mikayel Samvelyan, Mingfei Sun, Anuj Mahajan, Jakob N. Foerster, Shimon Whiteson
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning. CoRR (2022)
Risto Vuorio, Jacob Beck, Shimon Whiteson, Jakob N. Foerster, Gregory Farquhar
An Investigation of the Bias-Variance Tradeoff in Meta-Gradients. CoRR (2022)
Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, Pawan Kumar Mudigonda
In Defense of the Unitary Scalarization for Deep Multi-Task Learning. NeurIPS (2022)
Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Becca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, Sergey Levine
Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. CoRR (2022)
Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Shimon Whiteson
Hypernetworks in Meta-Reinforcement Learning. CoRR (2022)
Angad Singh, Omar Makhlouf, Maximilian Igl, João V. Messias, Arnaud Doucet, Shimon Whiteson
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving. CoRR (2022)
Eli Bronstein, Mark Palatucci, Dominik Notz, Brandyn White, Alex Kuefler, Yiren Lu, Supratik Paul, Payam Nikdel, Paul Mougin, Hongge Chen, Justin Fu, Austin Abrams, Punit Shah, Evan Racah, Benjamin Frenkel, Shimon Whiteson, Dragomir Anguelov
Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. IROS (2022)
Angad Singh, Omar Makhlouf, Maximilian Igl, João Messias, Arnaud Doucet, Shimon Whiteson
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving. CoRL (2022)
Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Shimon Whiteson
Hypernetworks in Meta-Reinforcement Learning. CoRL (2022)
Anuj Mahajan, Mikayel Samvelyan, Tarun Gupta, Benjamin Ellis, Mingfei Sun, Tim Rocktäschel, Shimon Whiteson
Generalization in Cooperative Multi-Agent Systems. CoRR (2022)
Eli Bronstein, Sirish Srinivasan, Supratik Paul, Aman Sinha, Matthew O'Kelly, Payam Nikdel, Shimon Whiteson
Embedding Synthetic Off-Policy Experience for Autonomous Driving via Zero-Shot Curricula. CoRL (2022)
Luisa M. Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. CoRR (2021)
Shangtong Zhang, Yi Wan, Richard S. Sutton, Shimon Whiteson
Average-Reward Off-Policy Policy Evaluation with Function Approximation. CoRR (2021)
Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson
Transient Non-stationarity and Generalisation in Deep Reinforcement Learning. ICLR (2021)
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Breaking the Deadly Triad with a Target Network. CoRR (2021)
Tonghan Wang, Tarun Gupta, Anuj Mahajan, Bei Peng, Shimon Whiteson, Chongjie Zhang
RODE: Learning Roles to Decompose Multi-Agent Tasks. ICLR (2021)
Mattie Fellows, Kristian Hartikainen, Shimon Whiteson
Bayesian Bellman Operators. NeurIPS (2021)
Mingfei Sun, Anuj Mahajan, Katja Hofmann, Shimon Whiteson
SoftDICE for Imitation Learning: Rethinking Off-policy Distribution Matching. CoRR (2021)
Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency. CoRR (2021)
Shangtong Zhang, Yi Wan, Richard S. Sutton, Shimon Whiteson
Average-Reward Off-Policy Policy Evaluation with Function Approximation. ICML (2021)
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Breaking the Deadly Triad with a Target Network. ICML (2021)
Shangtong Zhang, Bo Liu, Shimon Whiteson
Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning. AAAI (2021)
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. ICML (2021)
Guangliang Li, Hamdi Dibeklioglu, Shimon Whiteson, Hayley Hung
Facial Feedback for Reinforcement Learning: A Case Study and Offline Analysis Using the TAMER Framework. AAMAS (2021)
Luisa M. Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning. ICML (2021)
Vitaly Kurin, Maximilian Igl, Tim Rocktäschel, Wendelin Boehmer, Shimon Whiteson
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control. ICLR (2021)
Charles Blake, Vitaly Kurin, Maximilian Igl, Shimon Whiteson
Snowflake: Scaling GNNs to high-dimensional continuous control via parameter freezing. NeurIPS (2021)
Luisa M. Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. AAMAS (2021)
Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
Deep Residual Reinforcement Learning (Extended Abstract). IJCAI (2021)
Jacopo Castellini, Frans A. Oliehoek, Rahul Savani, Shimon Whiteson
Analysing factorizations of action-value networks for cooperative multi-agent reinforcement learning. Auton. Agents Multi Agent Syst. 35 (2) (2021)
Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha
Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning. ICML (2021)
Pascal Van Der Vaart, Anuj Mahajan, Shimon Whiteson
Model based Multi-agent Reinforcement Learning with Tensor Decompositions. CoRR (2021)
Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson
Regularized Softmax Deep Multi-Agent Q-Learning. NeurIPS (2021)
Bei Peng, Tabish Rashid, Christian Schröder de Witt, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson
FACMAC: Factored Multi-Agent Centralised Policy Gradients. NeurIPS (2021)
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. CoRR (2021)
Luisa M. Zintgraf, Sebastian Schulze, Cong Lu, Leo Feng, Maximilian Igl, Kyriacos Shiarlis, Yarin Gal, Katja Hofmann, Shimon Whiteson
VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning. J. Mach. Learn. Res. 22 (2021)
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar
Reinforcement Learning in Factored Action Spaces using Tensor Decompositions. CoRR (2021)
Dmitrii Beloborodov, Alexander E. Ulanov, Jakob N. Foerster, Shimon Whiteson, A. I. Lvovsky
Reinforcement learning enhanced quantum-inspired algorithm for combinatorial optimization. Mach. Learn. Sci. Technol. 2 (2) (2021)
Zheng Xiong, Luisa M. Zintgraf, Jacob Beck, Risto Vuorio, Shimon Whiteson
On the Practical Consistency of Meta-Reinforcement Learning Algorithms. CoRR (2021)
Samuel Sokota, Christian Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Shimon Whiteson, Jakob N. Foerster
Implicit Communication as Minimum Entropy Coupling. CoRR (2021)
Shangtong Zhang, Shimon Whiteson
Truncated Emphatic Temporal Difference Methods for Prediction and Control. CoRR (2021)
Bozhidar Vasilev, Tarun Gupta, Bei Peng, Shimon Whiteson
Semi-On-Policy Training for Sample Efficient Multi-Agent Policy Gradients. CoRR (2021)
Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson
Softmax with Regularization: Better Value Estimation in Multi-Agent Reinforcement Learning. CoRR (2021)
Matthew Fellows, Kristian Hartikainen, Shimon Whiteson
Bayesian Bellman Operators. CoRR (2021)
Charlie Blake, Vitaly Kurin, Maximilian Igl, Shimon Whiteson
Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing. CoRR (2021)
Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning. ICML (2021)
Shangtong Zhang, Bo Liu, Shimon Whiteson
Per-Step Reward: A New Perspective for Risk-Averse Reinforcement Learning. CoRR (2020)
Maximilian Igl, Andrew Gambardella, Jinke He, Nantas Nardelli, N. Siddharth, Wendelin Boehmer, Shimon Whiteson
Multitask Soft Option Learning. UAI (2020)
Supratik Paul, Konstantinos I. Chatzilygeroudis, Kamil Ciosek, Jean-Baptiste Mouret, Michael A. Osborne, Shimon Whiteson
Robust Reinforcement Learning with Bayesian Optimisation and Quadrature. J. Mach. Learn. Res. 21 (2020)
Vitaly Kurin, Saad Godil, Shimon Whiteson, Bryan Catanzaro
Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver? NeurIPS (2020)
Shangtong Zhang, Vivek Veeriah, Shimon Whiteson
Learning Retrospective Knowledge with Reverse Reinforcement Learning. CoRR (2020)
Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Böhmer, Shimon Whiteson, Fei Sha
AI-QMIX: Attention and Imagination for Dynamic Multi-Agent Reinforcement Learning. CoRR (2020)
Wendelin Boehmer, Vitaly Kurin, Shimon Whiteson
Deep Coordination Graphs. ICML (2020)

Shimon Whiteson.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Shimon Whiteson