Whiteson, Shimon

110 publications

NeurIPS 2025 A Clean Slate for Offline Reinforcement Learning Matthew Thomas Jackson, Uljad Berdica, Jarek Luca Liesen, Shimon Whiteson, Jakob Nicolaus Foerster

FnTML 2025 A Tutorial on Meta-Reinforcement Learning Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa M. Zintgraf, Chelsea Finn, Shimon Whiteson

NeurIPS 2025 GoalLadder: Incremental Goal Discovery with Vision-Language Models Alexey Zakharov, Shimon Whiteson

NeurIPS 2024 Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps Benjamin Ellis, Matthew T. Jackson, Andrei Lupu, Alexander D. Goldie, Mattie Fellows, Shimon Whiteson, Jakob N. Foerster

ICML 2024 Bayesian Exploration Networks Mattie Fellows, Brandon Gary Kaplowitz, Christian Schroeder De Witt, Shimon Whiteson

NeurIPS 2024 Can Learned Optimization Make Reinforcement Learning Less Difficult? Alexander D. Goldie, Chris Lu, Matthew T. Jackson, Shimon Whiteson, Jakob N. Foerster

ICMLW 2024 Can Learned Optimization Make Reinforcement Learning Less Difficult? Alexander D. Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob Nicolaus Foerster

ICLR 2024 Discovering Temporally-Aware Reinforcement Learning Algorithms Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

ICML 2024 Distilling Morphology-Conditioned Hypernetworks for Efficient Universal Morphology Control Zheng Xiong, Risto Vuorio, Jacob Beck, Matthieu Zimmer, Kun Shao, Shimon Whiteson

NeurIPSW 2024 Efficient Domain Adaptation of Robotic Foundation Models via Hypernetwork-Generated LoRA Zheng Xiong, Siddhant Sharma, Kang Li, Risto Vuorio, Shimon Whiteson

NeurIPS 2024 JaxMARL: Multi-Agent RL Environments and Algorithms in JAX Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Ravi Hammond, Akbir Khan, Christian Schroeder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Foerster

CoRL 2024 Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling Aman Sinha, Payam Nikdel, Supratik Paul, Shimon Whiteson

ICLR 2023 Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning Yat Long Lo, Christian Schroeder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson

NeurIPS 2023 Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design Matthew T Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Greg Farquhar, Shimon Whiteson, Jakob Foerster

NeurIPSW 2023 Discovering Temporally-Aware Reinforcement Learning Algorithms Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

NeurIPSW 2023 JaxMARL: Multi-Agent RL Environments in JAX Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schroeder 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

NeurIPS 2023 Recurrent Hypernetworks Are Surprisingly Strong in Meta-RL Jacob Beck, Risto Vuorio, Zheng Xiong, Shimon Whiteson

NeurIPS 2023 SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning Benjamin Ellis, Jonathan Cook, Skander Moalla, Mikayel Samvelyan, Mingfei Sun, Anuj Mahajan, Jakob Foerster, Shimon Whiteson

NeurIPS 2023 The Waymo Open Sim Agents Challenge Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nicholas Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Yang, Shimon Whiteson, Brandyn White, Dragomir Anguelov

ICML 2023 Universal Morphology Control via Contextual Modulation Zheng Xiong, Jacob Beck, Shimon Whiteson

ICML 2023 Why Target Networks Stabilise Temporal Difference Methods Mattie Fellows, Matthew J. A. Smith, Shimon Whiteson

ICML 2022 Communicating via Markov Decision Processes Samuel Sokota, Christian A Schroeder De Witt, Maximilian Igl, Luisa M Zintgraf, Philip Torr, Martin Strohmeier, Zico Kolter, Shimon Whiteson, Jakob Foerster

AAAI 2022 Deterministic and Discriminative Imitation (d2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson

CoRL 2022 Embedding Synthetic Off-Policy Experience for Autonomous Driving via Zero-Shot Curricula Eli Bronstein, Sirish Srinivasan, Supratik Paul, Aman Sinha, Matthew O’Kelly, Payam Nikdel, Shimon Whiteson

NeurIPS 2022 Equivariant Networks for Zero-Shot Coordination Darius Muglich, Christian Schroeder de Witt, Elise van der Pol, Shimon Whiteson, Jakob Foerster

ICML 2022 Generalized Beliefs for Cooperative AI Darius Muglich, Luisa M Zintgraf, Christian A Schroeder De Witt, Shimon Whiteson, Jakob Foerster

CoRL 2022 Hypernetworks in Meta-Reinforcement Learning Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Shimon Whiteson

NeurIPS 2022 In Defense of the Unitary Scalarization for Deep Multi-Task Learning Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, Pawan K Mudigonda

CoLLAs 2022 Learning Skills Diverse in Value-Relevant Features Matthew J. A. Smith, Jelena Luketina, Kristian Hartikainen, Maximilian Igl, Shimon Whiteson

CoRL 2022 Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving Angad Singh, Omar Makhlouf, Maximilian Igl, Joao Messias, Arnaud Doucet, Shimon Whiteson

JMLR 2022 Truncated Emphatic Temporal Difference Methods for Prediction and Control Shangtong Zhang, Shimon Whiteson

ICML 2021 Average-Reward Off-Policy Policy Evaluation with Function Approximation Shangtong Zhang, Yi Wan, Richard S Sutton, Shimon Whiteson

NeurIPS 2021 Bayesian Bellman Operators Mattie Fellows, Kristian Hartikainen, Shimon Whiteson

ICML 2021 Breaking the Deadly Triad with a Target Network Shangtong Zhang, Hengshuai Yao, Shimon Whiteson

IJCAI 2021 Deep Residual Reinforcement Learning (Extended Abstract) Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson

ICML 2021 Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning Luisa M Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson

NeurIPS 2021 FACMAC: Factored Multi-Agent Centralised Policy Gradients Bei Peng, Tabish Rashid, Christian Schroeder de Witt, Pierre-Alexandre Kamienny, Philip Torr, Wendelin Boehmer, Shimon Whiteson

AAAI 2021 Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning Shangtong Zhang, Bo Liu, Shimon Whiteson

ICLR 2021 My Body Is a Cage: The Role of Morphology in Graph-Based Incompatible Control Vitaly Kurin, Maximilian Igl, Tim Rocktäschel, Wendelin Boehmer, Shimon Whiteson

NeurIPSW 2021 No DICE: An Investigation of the Bias-Variance Tradeoff in Meta-Gradients Risto Vuorio, Jacob Austin Beck, Gregory Farquhar, Jakob Nicolaus Foerster, Shimon Whiteson

NeurIPSW 2021 On the Practical Consistency of Meta-Reinforcement Learning Algorithms Zheng Xiong, Luisa M Zintgraf, Jacob Austin Beck, Risto Vuorio, Shimon Whiteson

ICLR 2021 RODE: Learning Roles to Decompose Multi-Agent Tasks Tonghan Wang, Tarun Gupta, Anuj Mahajan, Bei Peng, Shimon Whiteson, Chongjie Zhang

ICML 2021 Randomized Entity-Wise Factorization for Multi-Agent Reinforcement Learning Shariq Iqbal, Christian A Schroeder De Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha

NeurIPS 2021 Regularized SoftMax Deep Multi-Agent Q-Learning Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson

NeurIPS 2021 Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing Charles Blake, Vitaly Kurin, Maximilian Igl, Shimon Whiteson

ICML 2021 Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar

ICLR 2021 Transient Non-Stationarity and Generalisation in Deep Reinforcement Learning Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson

ICML 2021 UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson

JMLR 2021 VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning Luisa Zintgraf, Sebastian Schulze, Cong Lu, Leo Feng, Maximilian Igl, Kyriacos Shiarlis, Yarin Gal, Katja Hofmann, Shimon Whiteson

NeurIPS 2020 Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver? Vitaly Kurin, Saad Godil, Shimon Whiteson, Bryan Catanzaro

ICML 2020 Deep Coordination Graphs Wendelin Boehmer, Vitaly Kurin, Shimon Whiteson

JMLR 2020 Expected Policy Gradients for Reinforcement Learning Kamil Ciosek, Shimon Whiteson

ICML 2020 GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values Shangtong Zhang, Bo Liu, Shimon Whiteson

ICML 2020 Growing Action Spaces Gregory Farquhar, Laura Gustafson, Zeming Lin, Shimon Whiteson, Nicolas Usunier, Gabriel Synnaeve

NeurIPS 2020 Learning Retrospective Knowledge with Reverse Reinforcement Learning Shangtong Zhang, Vivek Veeriah, Shimon Whiteson

JMLR 2020 Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning Tabish Rashid, Mikayel Samvelyan, Christian Schroeder de Witt, Gregory Farquhar, Jakob Foerster, Shimon Whiteson

UAI 2020 Multitask Soft Option Learning Maximilian Igl, Andrew Gambardella, Jinke He, Nantas Nardelli, N Siddharth, Wendelin Boehmer, Shimon Whiteson

ICLR 2020 Optimistic Exploration Even with a Pessimistic Initialisation Tabish Rashid, Bei Peng, Wendelin Böhmer, Shimon Whiteson

ICML 2020 Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson

JMLR 2020 Robust Reinforcement Learning with Bayesian Optimisation and Quadrature Supratik Paul, Konstantinos Chatzilygeroudis, Kamil Ciosek, Jean-Baptiste Mouret, Michael A. Osborne, Shimon Whiteson

ICLR 2020 VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson

NeurIPS 2020 Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning Tabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson

ICMLW 2020 WordCraft: An Environment for Benchmarking Commonsense Agents Minqi Jiang, Jelena Luketina, Nantas Nardelli, Pasquale Minervini, Philip Torr, Shimon Whiteson, Tim Rocktäschel

ICML 2019 A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs Jingkai Mao, Jakob Foerster, Tim Rocktäschel, Maruan Al-Shedivat, Gregory Farquhar, Shimon Whiteson

IJCAI 2019 A Survey of Reinforcement Learning Informed by Natural Language Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob N. Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, Tim Rocktäschel

ICML 2019 Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning Jakob Foerster, Francis Song, Edward Hughes, Neil Burch, Iain Dunning, Shimon Whiteson, Matthew Botvinick, Michael Bowling

NeurIPS 2019 DAC: The Double Actor-Critic Architecture for Learning Options Shangtong Zhang, Shimon Whiteson

ICML 2019 Fast Context Adaptation via Meta-Learning Luisa Zintgraf, Kyriacos Shiarli, Vitaly Kurin, Katja Hofmann, Shimon Whiteson

NeurIPS 2019 Fast Efficient Hyperparameter Tuning for Policy Gradient Methods Supratik Paul, Vitaly Kurin, Shimon Whiteson

ICMLW 2019 Fast Efficient Hyperparameter Tuning for Policy Gradients Supratik Paul, Vitaly Kurin, Shimon Whiteson

ICML 2019 Fingerprint Policy Optimisation for Robust Reinforcement Learning Supratik Paul, Michael A. Osborne, Shimon Whiteson

NeurIPS 2019 Generalized Off-Policy Actor-Critic Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson

NeurIPS 2019 Loaded DiCE: Trading Off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning Gregory Farquhar, Shimon Whiteson, Jakob Foerster

NeurIPS 2019 MAVEN: Multi-Agent Variational Exploration Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan, Shimon Whiteson

NeurIPS 2019 Multi-Agent Common Knowledge Reinforcement Learning Christian Schroeder de Witt, Jakob Foerster, Gregory Farquhar, Philip Torr, Wendelin Boehmer, Shimon Whiteson

ICLR 2019 Stable Opponent Shaping in Differentiable Games Alistair Letcher, Jakob Foerster, David Balduzzi, Tim Rocktäschel, Shimon Whiteson

NeurIPS 2019 VIREL: A Variational Inference Framework for Reinforcement Learning Matthew Fellows, Anuj Mahajan, Tim G. J. Rudner, Shimon Whiteson

AAAI 2018 Alternating Optimisation and Quadrature for Robust Control Supratik Paul, Konstantinos I. Chatzilygeroudis, Kamil Ciosek, Jean-Baptiste Mouret, Michael A. Osborne, Shimon Whiteson

AAAI 2018 Counterfactual Multi-Agent Policy Gradients Jakob N. Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, Shimon Whiteson

ICML 2018 Deep Variational Reinforcement Learning for POMDPs Maximilian Igl, Luisa Zintgraf, Tuan Anh Le, Frank Wood, Shimon Whiteson

ICML 2018 DiCE: The Infinitely Differentiable Monte Carlo Estimator Jakob Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric Xing, Shimon Whiteson

AAAI 2018 Expected Policy Gradients Kamil Ciosek, Shimon Whiteson

ICML 2018 Fourier Policy Gradients Matthew Fellows, Kamil Ciosek, Shimon Whiteson

ICML 2018 QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning Tabish Rashid, Mikayel Samvelyan, Christian Schroeder, Gregory Farquhar, Jakob Foerster, Shimon Whiteson

ICML 2018 TACO: Learning Task Decomposition via Temporal Alignment for Control Kyriacos Shiarlis, Markus Wulfmeier, Sasha Salter, Shimon Whiteson, Ingmar Posner

ICLR 2018 TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning Gregory Farquhar, Tim Rocktäschel, Maximilian Igl, Shimon Whiteson

NeurIPS 2017 Dynamic-Depth Context Tree Weighting Joao V Messias, Shimon Whiteson

AAAI 2017 OFFER: Off-Environment Reinforcement Learning Kamil Andrzej Ciosek, Shimon Whiteson

UAI 2017 Real-Time Resource Allocation for Tracking Systems Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, Henri Bouma

ICML 2017 Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning Jakob Foerster, Nantas Nardelli, Gregory Farquhar, Triantafyllos Afouras, Philip H. S. Torr, Pushmeet Kohli, Shimon Whiteson

NeurIPS 2016 Learning to Communicate with Deep Multi-Agent Reinforcement Learning Jakob Foerster, Ioannis Alexandros Assael, Nando de Freitas, Shimon Whiteson

IJCAI 2016 PAC Greedy Maximization with Efficient Bounds on Information Gain for Sensor Selection Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek

JAIR 2015 Computing Convex Coverage Sets for Faster Multi-Objective Coordination Diederik Marijn Roijers, Shimon Whiteson, Frans A. Oliehoek

NeurIPS 2015 Copeland Dueling Bandits Masrour Zoghi, Zohar S Karnin, Shimon Whiteson, Maarten de Rijke

AAAI 2015 Exploiting Submodular Value Functions for Faster Dynamic Sensor Selection Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek

IJCAI 2015 Point-Based Planning for Multi-Objective POMDPs Diederik Marijn Roijers, Shimon Whiteson, Frans A. Oliehoek

ICML 2014 Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem Masrour Zoghi, Shimon Whiteson, Remi Munos, Maarten Rijke

JAIR 2013 A Survey of Multi-Objective Sequential Decision-Making Diederik M. Roijers, Peter Vamplew, Shimon Whiteson, Richard Dazeley

JAIR 2013 Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs Frans A. Oliehoek, Matthijs T. J. Spaan, Christopher Amato, Shimon Whiteson

UAI 2012 Exploiting Structure in Cooperative Bayesian Games Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J. Spaan

JMLR 2011 Exploiting Best-Match Equations for Efficient Reinforcement Learning Harm van Seijen, Shimon Whiteson, Hado van Hasselt, Marco Wiering

MLJ 2011 Introduction to the Special Issue on Empirical Evaluations in Reinforcement Learning Shimon Whiteson, Michael L. Littman

ECML-PKDD 2008 Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs Lior Kuyer, Shimon Whiteson, Bram Bakker, Nikos Vlassis

AAAI 2007 Stochastic Optimization for Collision Selection in High Energy Physics Shimon Whiteson, Daniel Whiteson

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

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

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

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

AAAI 2005 Improving Reinforcement Learning Function Approximators via Neuroevolution Shimon Whiteson

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