← Authors

Shimon Whiteson

80 papers · 2006–2024 · 8 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (8) 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (19) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (18) 🌈 Renaissance Researcher (9) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (3) 🏠 Conference Loyalist (26) 🀝 Dynamic Duo (17) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (7) πŸ† Grand Slam πŸ‘₯ Mega-Team (21) 🧬 Topic Evolution πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (11) ❓ The Questioner (2) πŸ’Ž Century Club (80) πŸ—ƒοΈ Keyword Collector (83) ⚑ Prolific Year (9)

Conferences

ICML (27) NIPS (26) ICLR (9) JMLR (7) CORL (4) IJCAI (4) AAAI (2) UAI (1)

Top co-authors

Jakob Foerster (17) Gregory Farquhar (12) Maximilian Igl (11) Wendelin Boehmer (11) Shangtong Zhang (10) Vitaly Kurin (7) Bei Peng (7) Christian Schroeder de Witt (7) Tim RocktΓ€schel (7) Tabish Rashid (7)

Keywords

multi-agent reinforcement learning (15) reinforcement learning (9) off-policy learning (8) function approximation (7) deep reinforcement learning (5) policy gradient (5) sample efficiency (5) value function (5) target network (4) temporal difference learning (4) continuous control (4) imitation learning (4) multi-agent system (4) meta-reinforcement learning (3) cooperative multi-agent (3) off-policy reinforcement learning (3) multi-task learning (3) curriculum learning (3) variance reduction (3) partial observability (3)

Papers

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