Shimon Whiteson

Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps NeurIPS 2024 Bayesian Exploration Networks ICML 2024 Can Learned Optimization Make Reinforcement Learning Less Difficult? NeurIPS 2024 Discovering Temporally-Aware Reinforcement Learning Algorithms ICLR 2024 Distilling Morphology-Conditioned Hypernetworks for Efficient Universal Morphology Control ICML 2024 JaxMARL: Multi-Agent RL Environments and Algorithms in JAX NeurIPS 2024 Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling CoRL 2024 Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning ICLR 2023 Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design NeurIPS 2023 Recurrent Hypernetworks are Surprisingly Strong in Meta-RL NeurIPS 2023 SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning NeurIPS 2023 The Waymo Open Sim Agents Challenge NeurIPS 2023 Universal Morphology Control via Contextual Modulation ICML 2023 Why Target Networks Stabilise Temporal Difference Methods ICML 2023 Communicating via Markov Decision Processes ICML 2022 Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency AAAI 2022 Embedding Synthetic Off-Policy Experience for Autonomous Driving via Zero-Shot Curricula CoRL 2022 Equivariant Networks for Zero-Shot Coordination NeurIPS 2022 Generalized Beliefs for Cooperative AI ICML 2022 Hypernetworks in Meta-Reinforcement Learning CoRL 2022 In Defense of the Unitary Scalarization for Deep Multi-Task Learning NeurIPS 2022 Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving CoRL 2022 Truncated Emphatic Temporal Difference Methods for Prediction and Control JMLR 2022 Average-Reward Off-Policy Policy Evaluation with Function Approximation ICML 2021 Bayesian Bellman Operators NeurIPS 2021 Breaking the Deadly Triad with a Target Network ICML 2021 Deep Residual Reinforcement Learning (Extended Abstract) IJCAI 2021 Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning ICML 2021 FACMAC: Factored Multi-Agent Centralised Policy Gradients NeurIPS 2021 Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning AAAI 2021 My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control ICLR 2021 Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning ICML 2021 Regularized Softmax Deep Multi-Agent Q-Learning NeurIPS 2021 RODE: Learning Roles to Decompose Multi-Agent Tasks ICLR 2021 Snowflake: Scaling GNNs to high-dimensional continuous control via parameter freezing NeurIPS 2021 Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning ICML 2021 Transient Non-stationarity and Generalisation in Deep Reinforcement Learning ICLR 2021 UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning ICML 2021 VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning JMLR 2021 Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver? NeurIPS 2020 Deep Coordination Graphs ICML 2020 Expected Policy Gradients for Reinforcement Learning JMLR 2020 GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values ICML 2020 Growing Action Spaces ICML 2020 Learning Retrospective Knowledge with Reverse Reinforcement Learning NeurIPS 2020 Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning JMLR 2020 Multitask Soft Option Learning UAI 2020 Optimistic Exploration even with a Pessimistic Initialisation ICLR 2020 Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation ICML 2020 Robust Reinforcement Learning with Bayesian Optimisation and Quadrature JMLR 2020 VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning ICLR 2020 Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning NeurIPS 2020 A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs ICML 2019 A Survey of Reinforcement Learning Informed by Natural Language IJCAI 2019 Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning ICML 2019 DAC: The Double Actor-Critic Architecture for Learning Options NeurIPS 2019 Fast Context Adaptation via Meta-Learning ICML 2019 Fast Efficient Hyperparameter Tuning for Policy Gradient Methods NeurIPS 2019 Fingerprint Policy Optimisation for Robust Reinforcement Learning ICML 2019 Generalized Off-Policy Actor-Critic NeurIPS 2019 Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning NeurIPS 2019 MAVEN: Multi-Agent Variational Exploration NeurIPS 2019 Multi-Agent Common Knowledge Reinforcement Learning NeurIPS 2019 Stable Opponent Shaping in Differentiable Games ICLR 2019 VIREL: A Variational Inference Framework for Reinforcement Learning NeurIPS 2019 Deep Variational Reinforcement Learning for POMDPs ICML 2018 DiCE: The Infinitely Differentiable Monte Carlo Estimator ICML 2018 Fourier Policy Gradients ICML 2018 QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning ICML 2018 TACO: Learning Task Decomposition via Temporal Alignment for Control ICML 2018 TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning ICLR 2018 Dynamic-Depth Context Tree Weighting NeurIPS 2017 Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning ICML 2017 Learning to Communicate with Deep Multi-Agent Reinforcement Learning NeurIPS 2016 PAC Greedy Maximization with Efficient Bounds on Information Gain for Sensor Selection IJCAI 2016 Copeland Dueling Bandits NeurIPS 2015 Point-Based Planning for Multi-Objective POMDPs IJCAI 2015 Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem ICML 2014 Exploiting Best-Match Equations for Efficient Reinforcement Learning JMLR 2011 Evolutionary Function Approximation for Reinforcement Learning JMLR 2006