Shimon Whiteson

发表

Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation

Alex Kuefler, B. White, Mark Palatucci, 2022, 2022 International Conference on Robotics and Automation (ICRA).

Generalized Beliefs for Cooperative AI

Luisa M. Zintgraf, Jakob N. Foerster, C. S. D. Witt, 2022, ICML.

Stochastic Optimization for Collision Selection in High Energy Physics

D. Whiteson, Shimon Whiteson, 2006, AAAI.

Communicating via Markov Decision Processes

Philip H. S. Torr, J. Z. Kolter, Luisa M. Zintgraf, 2021, International Conference on Machine Learning.

Monotonic Improvement Guarantees under Non-stationarity for Decentralized PPO

M. Sun, Sam Devlin, Katja Hofmann, 2022, ArXiv.

An Investigation of the Bias-Variance Tradeoff in Meta-Gradients

Jakob N. Foerster, Gregory Farquhar, Risto Vuorio, 2022, arXiv.org.

Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning

Shimon Whiteson, Marco Wiering, Harm van Seijen, 2009 .

In Defense of the Unitary Scalarization for Deep Multi-Task Learning

M. P. Kumar, Ilya Kostrikov, Vitaly Kurin, 2022, Neural Information Processing Systems.

Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving

Justin Fu, Alex Kuefler, B. White, 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Hypernetworks in Meta-Reinforcement Learning

Risto Vuorio, Shimon Whiteson, Jacob Beck, 2022, CoRL.

Communicating via Markov Decision Processes

Philip H. S. Torr, J. Z. Kolter, Luisa M. Zintgraf, 2021, ICML.

UvA-DARE (Digital Academic Repository) Towards Personalised Gaming via Facial Expression Recognition

Chek Tien Tan, Diederik M. Roijers, S. Whiteson, 2014 .

Equivariant Networks for Zero-Shot Coordination

Elise van der Pol, C. S. D. Witt, Shimon Whiteson, 2022, NeurIPS.

SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning

M. Sun, Mikayel Samvelyan, Shimon Whiteson, 2022, ArXiv.

A Survey of Meta-Reinforcement Learning

Chelsea Finn, E. Liu, Zheng Xiong, 2023, ArXiv.

Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency

Sam Devlin, Katja Hofmann, Shimon Whiteson, 2021, AAAI.

SoftDICE for Imitation Learning: Rethinking Off-policy Distribution Matching pdf

Shimon Whiteson, Katja Hofmann, Anuj Mahajan, 2021, ArXiv.

Analysing factorizations of action-value networks for cooperative multi-agent reinforcement learning

Shimon Whiteson, Rahul Savani, Frans A. Oliehoek, 2019, Autonomous Agents and Multi-Agent Systems.

Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning pdf

H. Francis Song, Shimon Whiteson, Michael H. Bowling, 2018, ICML.

Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks pdf

Shimon Whiteson, Nando de Freitas, Jakob N. Foerster, 2016, ArXiv.

Deep Variational Reinforcement Learning for POMDPs

Shimon Whiteson, Tuan Anh Le, Frank Wood, 2018, ICML.

Traffic Light Control by Multiagent Reinforcement Learning Systems

Shimon Whiteson, Frans C. A. Groen, Leon J. H. M. Kester, 2010, Interactive Collaborative Information Systems.

Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs

Shimon Whiteson, Frans A. Oliehoek, Matthijs T. J. Spaan, 2013, J. Artif. Intell. Res..

Incremental clustering and expansion for faster optimal planning in decentralized POMDPs

Frans A. Oliehoek, S. Whiteson, F. Oliehoek, 2013 .

A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms

Shangtong Zhang, H. V. Seijen, R. Laroche, 2020, AAMAS.

Dynamic-Depth Context Tree Weighting

Shimon Whiteson, João V. Messias, J. Messias, 2017, NIPS.

EFFICIENT ABSTRACTION SELECTION IN REINFORCEMENT LEARNING

Shimon Whiteson, Harm van Seijen, Leon J. H. M. Kester, 2013, Comput. Intell..

Efficient Abstraction Selection in Reinforcement Learning (Extended Abstract)

Shimon Whiteson, Harm van Seijen, Leon J. H. M. Kester, 2013, SARA.

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning pdf

Shimon Whiteson, Jakob N. Foerster, Gregory Farquhar, 2018, ICML.

Counterfactual Multi-Agent Policy Gradients

Shimon Whiteson, Triantafyllos Afouras, Jakob N. Foerster, 2017, AAAI.

Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning

Shimon Whiteson, Pushmeet Kohli, Philip H. S. Torr, 2017, ICML.

Expected Policy Gradients

Shimon Whiteson, Kamil Ciosek, K. Ciosek, 2017, AAAI.

UvA-DARE ( Digital Academic Repository ) Learning Potential Functions and their Representations for MultiTask Reinforcement Learning

S. Whiteson, M. Snel, Shimon Whiteson, 2014 .

Learning potential functions and their representations for multi-task reinforcement learning

Shimon Whiteson, Matthijs Snel, M. Snel, 2013, Autonomous Agents and Multi-Agent Systems.

Growing Action Spaces pdf

Shimon Whiteson, Nicolas Usunier, Gregory Farquhar, 2019, ICML.

Queued Pareto Local Search for Multi-Objective Optimization

Shimon Whiteson, Diederik M. Roijers, Chiel Kooijman, 2014, PPSN.

Critical factors in the empirical performance of temporal difference and evolutionary methods for reinforcement learning

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2010, Autonomous Agents and Multi-Agent Systems.

Empirical Studies in Action Selection with Reinforcement Learning

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2007, Adapt. Behav..

MAVEN: Multi-Agent Variational Exploration

Shimon Whiteson, Anuj Mahajan, Tabish Rashid, 2019, NeurIPS.

Multi-Agent Common Knowledge Reinforcement Learning

Shimon Whiteson, Philip H. S. Torr, Jakob N. Foerster, 2018, NeurIPS.

WordCraft: An Environment for Benchmarking Commonsense Agents pdf

Shimon Whiteson, Philip H. S. Torr, Pasquale Minervini, 2020, ArXiv.

Fast Context Adaptation via Meta-Learning

Katja Hofmann, Shimon Whiteson, Vitaly Kurin, 2018, ICML.

Truncated Emphatic Temporal Difference Methods for Prediction and Control

S. Whiteson, Shangtong Zhang, Shimon Whiteson, 2021, J. Mach. Learn. Res..

Neuroevolutionary reinforcement learning for generalized helicopter control

Shimon Whiteson, Rogier Koppejan, S. Whiteson, 2009, GECCO.

LipNet: End-to-End Sentence-level Lipreading

Shimon Whiteson, Nando de Freitas, Brendan Shillingford, 2016, 1611.01599.

LipNet: Sentence-level Lipreading pdf

Shimon Whiteson, Nando de Freitas, Brendan Shillingford, 2016, ArXiv.

Learning with Opponent-Learning Awareness pdf

Shimon Whiteson, Pieter Abbeel, Jakob N. Foerster, 2017, AAMAS.

Deep Residual Reinforcement Learning (Extended Abstract)

Shimon Whiteson, Shangtong Zhang, Wendelin Boehmer, 2021, IJCAI.

Critical factors in the performance of novelty search

Shimon Whiteson, Steijn Kistemaker, Shimon Whiteson, 2011, GECCO '11.

Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem pdf

M. de Rijke, Shimon Whiteson, Maarten de Rijke, 2013, ICML.

Alternating Optimisation and Quadrature for Robust Control

Shimon Whiteson, Michael A. Osborne, Jean-Baptiste Mouret, 2016, AAAI.

Learning to Communicate with Deep Multi-Agent Reinforcement Learning

Shimon Whiteson, Nando de Freitas, Jakob N. Foerster, 2016, NIPS.

Exploration with Unreliable Intrinsic Reward in Multi-Agent Reinforcement Learning pdf

Shimon Whiteson, Wendelin Böhmer, Tabish Rashid, 2019, ArXiv.

Transient Non-stationarity and Generalisation in Deep Reinforcement Learning

Shimon Whiteson, Gregory Farquhar, Jelena Luketina, 2020, ICLR.

TACO: Learning Task Decomposition via Temporal Alignment for Control pdf

Shimon Whiteson, Markus Wulfmeier, Ingmar Posner, 2018, ICML.

In Defense of the Unitary Scalarization for Deep Multi-Task Learning

M. P. Kumar, Ilya Kostrikov, Vitaly Kurin, 2022, NeurIPS.

VIREL: A Variational Inference Framework for Reinforcement Learning

Matthew Fellows, Shimon Whiteson, Anuj Mahajan, 2018, NeurIPS.

Generalization in Cooperative Multi-Agent Systems

Tim Rocktaschel, Mikayel Samvelyan, Shimon Whiteson, 2022, ArXiv.

Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning

Shimon Whiteson, Katja Hofmann, Luisa Zintgraf, 2020, ICML.

VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Luisa M. Zintgraf, S. Whiteson, Y. Gal, 2019, ICLR.

A Survey of Reinforcement Learning Informed by Natural Language

Shimon Whiteson, Jacob Andreas, Edward Grefenstette, 2019, IJCAI.

Protecting against evaluation overfitting in empirical reinforcement learning

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2011, 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).

Multi-Task Reinforcement Learning: Shaping and Feature Selection

Shimon Whiteson, Matthijs Snel, M. Snel, 2011, EWRL.

Exploiting submodular value functions for scaling up active perception

Shimon Whiteson, Frans A. Oliehoek, Matthijs T. J. Spaan, 2017, Autonomous Robots.

Exploiting Submodular Value Functions for Faster Dynamic Sensor Selection

Shimon Whiteson, Frans A. Oliehoek, Yash Satsangi, 2015, AAAI.

An Analysis of Piecewise-Linear and Convex Value Functions for Active Perception POMDPs

Shimon Whiteson, Matthijs T. J. Spaan, Yash Satsangi, 2015 .

Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning

Shimon Whiteson, Yuke Zhu, Jean Kossaifi, 2021, ICML.

Deep Interactive Bayesian Reinforcement Learning via Meta-Learning

K. Ciosek, Sam Devlin, Katja Hofmann, 2021, AAMAS.

VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning

Y. Gal, K. Shiarlis, Maximilian Igl, 2021, J. Mach. Learn. Res..

Maximizing Information Gain in Partially Observable Environments via Prediction Reward pdf

Shimon Whiteson, Frans A. Oliehoek, Martha White, 2020, AAMAS.

Multi-Objective Decision Making

Shimon Whiteson, Diederik M. Roijers, Shimon Whiteson, 2017, Synthesis Lectures on Artificial Intelligence and Machine Learning.

Point-Based Planning for Multi-Objective POMDPs

Shimon Whiteson, Frans A. Oliehoek, Diederik M. Roijers, 2015, IJCAI.

Linear support for multi-objective coordination graphs

Shimon Whiteson, Frans A. Oliehoek, Diederik M. Roijers, 2014, AAMAS.

A Survey of Multi-Objective Sequential Decision-Making pdf

Shimon Whiteson, Diederik M. Roijers, Peter Vamplew, 2013, J. Artif. Intell. Res..

Exploiting Structure in Cooperative Bayesian Games

Shimon Whiteson, Frans A. Oliehoek, Matthijs T. J. Spaan, 2012, UAI.

Exploiting Agent and Type Independence in Collaborative Graphical Bayesian Games pdf

Shimon Whiteson, Frans A. Oliehoek, Matthijs T. J. Spaan, 2011, ArXiv.

Integrating distributed Bayesian inference and reinforcement learning for sensor management

Shimon Whiteson, Gregor Pavlin, Bram Bakker, 2009, 2009 12th International Conference on Information Fusion.

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

Tim Rocktäschel, Vitaly Kurin, Maximilian Igl, 2020, ICLR.

Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?

Shimon Whiteson, Bryan Catanzaro, Vitaly Kurin, 2020, NeurIPS.

Deep Residual Reinforcement Learning

Shimon Whiteson, Wendelin Boehmer, Shangtong Zhang, 2019, AAMAS.

Machine learning for event selection in high energy physics

Shimon Whiteson, Daniel Whiteson, D. Whiteson, 2009, Eng. Appl. Artif. Intell..

GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values

S. Whiteson, Shangtong Zhang, Bo Liu, 2020, ICML.

Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control

Philip H. S. Torr, S. Whiteson, Wendelin Böhmer, 2020, ArXiv.

Regularized Softmax Deep Multi-Agent Q-Learning

Shimon Whiteson, Longbo Huang, Bei Peng, 2021, NeurIPS.

Softmax with Regularization: Better Value Estimation in Multi-Agent Reinforcement Learning pdf

Shimon Whiteson, Longbo Huang, Bei Peng, 2021, ArXiv.

Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge? pdf

Shimon Whiteson, Philip H. S. Torr, Philip H.S. Torr, 2020, ArXiv.

Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning pdf

Shimon Whiteson, Gregory Farquhar, Christian Schroeder de Witt, 2020, J. Mach. Learn. Res..

Weighted QMIX: Expanding Monotonic Value Function Factorisation pdf

Shimon Whiteson, Gregory Farquhar, Bei Peng, 2020, ArXiv.

Deep Coordination Graphs

S. Whiteson, Wendelin Böhmer, Vitaly Kurin, 2019, ICML.

The StarCraft Multi-Agent Challenge pdf

Shimon Whiteson, Philip H. S. Torr, Jakob N. Foerster, 2019, AAMAS.

Evolutionary Function Approximation for Reinforcement Learning

Shimon Whiteson, Peter Stone, S. Whiteson, 2006, J. Mach. Learn. Res..

Universal Morphology Control via Contextual Modulation

Zheng Xiong, Shimon Whiteson, Jacob Beck, 2023, ArXiv.

Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs

Shimon Whiteson, Nikos A. Vlassis, Bram Bakker, 2008, ECML/PKDD.

Robust central pattern generators for embodied hierarchical reinforcement learning

Yasuo Kuniyoshi, Shimon Whiteson, Matthijs Snel, 2011, 2011 IEEE International Conference on Development and Learning (ICDL).

Approximate solutions for factored Dec-POMDPs with many agents

Shimon Whiteson, Frans A. Oliehoek, Matthijs T. J. Spaan, 2013, AAMAS.

Towards Personalised Gaming via Facial Expression Recognition

Shimon Whiteson, Theo Gevers, Chek Tien Tan, 2014, AIIDE.

Challenge balancing for personalised game spaces

Shimon Whiteson, Sander Bakkes, Guangliang Li, 2014, 2014 IEEE Games Media Entertainment.

Towards Personalised Gaming via Facial Expression Recognition

Chek Tien Tan, Diederik M. Roijers, T. Gevers, 2014, Artificial Intelligence and Interactive Digital Entertainment Conference.

Towards Challenge Balancing for Personalised Game Spaces

Shimon Whiteson, Sander Bakkes, S. Bakkes, 2014 .

Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning

C. S. D. Witt, Samuel Sokota, Shimon Whiteson, 2023, ArXiv.

Social interaction for efficient agent learning from human reward

Shimon Whiteson, Hayley Hung, W. Bradley Knox, 2017, Autonomous Agents and Multi-Agent Systems.

Using informative behavior to increase engagement while learning from human reward

Shimon Whiteson, Hayley Hung, W. Bradley Knox, 2015, Autonomous Agents and Multi-Agent Systems.

Expected Policy Gradients for Reinforcement Learning pdf

Shimon Whiteson, Kamil Ciosek, K. Ciosek, 2018, J. Mach. Learn. Res..

A theoretical and empirical analysis of Expected Sarsa

Shimon Whiteson, Marco Wiering, Harm van Seijen, 2009, 2009 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning.

Learning From Demonstration in the Wild

Xi Chen, Shimon Whiteson, Frans A. Oliehoek, 2018, 2019 International Conference on Robotics and Automation (ICRA).

Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios

S. Levine, G. Tucker, Justin Fu, 2022, ArXiv.

TERESA: a socially intelligent semi-autonomous telepresence system

Gwenn Englebienne, Shimon Whiteson, Maja Pantic, 2015 .

Exploiting locality of interaction in factored Dec-POMDPs

Shimon Whiteson, Nikos A. Vlassis, Frans A. Oliehoek, 2008, AAMAS.

DAC: The Double Actor-Critic Architecture for Learning Options

Shimon Whiteson, Shangtong Zhang, Shangtong Zhang, 2019, NeurIPS.

Weighted QMIX: Expanding Monotonic Value Function Factorisation

Shimon Whiteson, Gregory Farquhar, Bei Peng, 2020, NeurIPS.

Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing pdf

Shimon Whiteson, Vitaly Kurin, Charlie Blake, 2021, NeurIPS.

UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning

Wendelin Böhmer, Bei Peng, Shimon Whiteson, 2020, ICML.

RODE: Learning Roles to Decompose Multi-Agent Tasks pdf

Shimon Whiteson, Bei Peng, Anuj Mahajan, 2020, ICLR.

Reinforcement Learning in Factored Action Spaces using Tensor Decompositions pdf

Shimon Whiteson, Jean Kossaifi, Animashree Anandkumar, 2021, ArXiv.

Adaptive Representations for Reinforcement Learning

Shimon Whiteson, S. Whiteson, Shimon Whiteson, 2010, Studies in Computational Intelligence.

OFFER: Off-Environment Reinforcement Learning

Shimon Whiteson, Kamil Andrzej Ciosek, K. Ciosek, 2017, AAAI.

Off-Environment RL with Rare Events

K. Ciosek, Shimon Whiteson, 2016 .

Evolutionary Computation for Reinforcement Learning

Shimon Whiteson, Shimon Whiteson, 2012, Reinforcement Learning.

FACMAC: Factored Multi-Agent Centralised Policy Gradients pdf

Shimon Whiteson, Wendelin Böhmer, Philip H. S. Torr, 2020, NeurIPS.

The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning

Shimon Whiteson, Rahul Savani, Frans A. Oliehoek, 2019, AAMAS.

The Impact of Non-stationarity on Generalisation in Deep Reinforcement Learning pdf

Shimon Whiteson, Gregory Farquhar, Jelena Luketina, 2020, ArXiv.

Multi-Objective Deep Reinforcement Learning pdf

Shimon Whiteson, Diederik M. Roijers, Yannis M. Assael, 2016, ArXiv.

Neuroevolutionary reinforcement learning for generalized control of simulated helicopters

Shimon Whiteson, Rogier Koppejan, S. Whiteson, 2011, Evol. Intell..

Fidelity, Soundness, and Efficiency of Interleaved Comparison Methods

Katja Hofmann, M. de Rijke, Shimon Whiteson, 2013, TOIS.

TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning

Shimon Whiteson, Gregory Farquhar, Tim Rocktäschel, 2017, ICLR.

TreeQN and ATreeC: Differentiable Tree Planning for Deep Reinforcement Learning pdf

Shimon Whiteson, Gregory Farquhar, Tim Rocktäschel, 2017, ICLR 2018.

Alternating Optimisation and Quadrature for Robust Reinforcement Learning pdf

Shimon Whiteson, Michael A. Osborne, Supratik Paul, 2016, ArXiv.

Robust Reinforcement Learning with Bayesian Optimisation and Quadrature

Shimon Whiteson, Michael A. Osborne, Supratik Paul, 2020, J. Mach. Learn. Res..

Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning

Shimon Whiteson, Bei Peng, Fei Sha, 2020, ICML.

Optimistic Exploration even with a Pessimistic Initialisation pdf

Shimon Whiteson, Wendelin Böhmer, Bei Peng, 2020, ICLR.

Improving SAT Solver Heuristics with Graph Networks and Reinforcement Learning pdf

Shimon Whiteson, Bryan Catanzaro, Vitaly Kurin, 2019, ArXiv.

Reinforcement learning enhanced quantum-inspired algorithm for combinatorial optimization

Shimon Whiteson, Jakob N. Foerster, University of Oxford, 2020, Mach. Learn. Sci. Technol..

Bayesian Bellman Operators pdf

Shimon Whiteson, Kristian Hartikainen, Matthew Fellows, 2021, NeurIPS.

PAC Greedy Maximization with Efficient Bounds on Information Gain for Sensor Selection

Shimon Whiteson, Frans A. Oliehoek, Yash Satsangi, 2016, IJCAI.

Probably Approximately Correct Greedy Maximization pdf

Shimon Whiteson, Frans A. Oliehoek, Yash Satsangi, 2016, ArXiv.

Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning

Shimon Whiteson, Shangtong Zhang, Bo Liu, 2020, AAAI.

Lossless clustering of histories in decentralized POMDPs

Shimon Whiteson, Frans A. Oliehoek, Matthijs T. J. Spaan, 2009, AAMAS.

On the Practical Consistency of Meta-Reinforcement Learning Algorithms pdf

Shimon Whiteson, Risto Vuorio, Luisa Zintgraf, 2021, ArXiv.

AI-QMIX: Attention and Imagination for Dynamic Multi-Agent Reinforcement Learning pdf

Shimon Whiteson, Fei Sha, Bei Peng, 2020, ArXiv.

Adaptive Tile Coding for Value Function Approximation

S. Whiteson, Shimon Whiteson, 2007 .

Reusing historical interaction data for faster online learning to rank for IR

Katja Hofmann, M. de Rijke, Shimon Whiteson, 2013, DIR.

Information Retrieval manuscript No. (will be inserted by the editor) Balancing Exploration and Exploitation in Listwise and Pairwise Online Learning to Rank for Information Retrieval

Katja Hofmann, M. de Rijke, Shimon Whiteson, 2022 .

Stable Opponent Shaping in Differentiable Games pdf

Shimon Whiteson, Jakob N. Foerster, David Balduzzi, 2018, ICLR.

The Reinforcement Learning Competitions

Shimon Whiteson, Brian Tanner, Adam M. White, 2010 .

Inverse Reinforcement Learning from Failure

Shimon Whiteson, João V. Messias, Kyriacos Shiarlis, 2016, AAMAS.

Adaptive job routing and scheduling

Shimon Whiteson, Peter Stone, P. Stone, 2004, Eng. Appl. Artif. Intell..

"Learning to rank for information retrieval from user interactions" by K. Hofmann, S. Whiteson, A. Schuth, and M. de Rijke with Martin Vesely as coordinator

Katja Hofmann, M. de Rijke, Shimon Whiteson, 2014, SIGWEB Newsl..

Supplementary Material: Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning

Fei Sha, Wendelin Böhmer, Bei Peng, 2021 .

Trust Region Bounds for Decentralized PPO Under Non-stationarity

Sam Devlin, Katja Hofmann, Shimon Whiteson, 2022, AAMAS.

Model based Multi-agent Reinforcement Learning with Tensor Decompositions pdf

Shimon Whiteson, Anuj Mahajan, Pascal Van Der Vaart, 2021, ArXiv.

Implicit Communication as Minimum Entropy Coupling pdf

Shimon Whiteson, Philip H. S. Torr, Samuel Sokota, 2021, ArXiv.

Semi-On-Policy Training for Sample Efficient Multi-Agent Policy Gradients pdf

Shimon Whiteson, Bei Peng, Tarun Gupta, 2021, ArXiv.

Monotonic Improvement Guarantees under Non-stationarity for Decentralized PPO

Sam Devlin, Katja Hofmann, Shimon Whiteson, 2022, ArXiv.

The StarCraft Multi-Agent Challenge Extended Abstract

Philip H. S. Torr, Jakob N. Foerster, Tim G. J. Rudner, 2019 .

DiCE: The Infinitely Differentiable Monte-Carlo Estimator pdf

Shimon Whiteson, Eric P. Xing, Jakob N. Foerster, 2018, ICML.

Stable Opponent Shaping in Differentiable Games

Jakob N. Foerster, S. Whiteson, Tim Rocktäschel, 2018, ICLR.

Multitask Soft Option Learning

Shimon Whiteson, Wendelin Böhmer, N. Siddharth, 2019, UAI.

Breaking the Deadly Triad with a Target Network

Hengshuai Yao, Shangtong Zhang, Shimon Whiteson, 2021, ICML.

Copeland Dueling Bandits

M. de Rijke, Shimon Whiteson, Maarten de Rijke, 2015, NIPS.

Relative confidence sampling for efficient on-line ranker evaluation

M. de Rijke, Shimon Whiteson, Maarten de Rijke, 2014, WSDM.

Probably Approximately Correct Greedy Maximization with Efficient Bounds on Information Gain for Sensor Selection

Shimon Whiteson, Frans A. Oliehoek, Yash Satsangi, 2016 .

Why Target Networks Stabilise Temporal Difference Methods

Shimon Whiteson, Matt Fellows, Matthew Smith, 2023, ArXiv.

Average-Reward Off-Policy Policy Evaluation with Function Approximation

R. Sutton, Shangtong Zhang, Yi Wan, 2021, ICML.

Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation

Hengshuai Yao, S. Whiteson, Shangtong Zhang, 2019, ICML.

Fast Efficient Hyperparameter Tuning for Policy Gradients pdf

Shimon Whiteson, Supratik Paul, Vitaly Kurin, 2019, NeurIPS.

Embedding Synthetic Off-Policy Experience for Autonomous Driving via Zero-Shot Curricula

Matthew O'Kelly, Supratik Paul, Shimon Whiteson, 2022, Conference on Robot Learning.

Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios

S. Levine, G. Tucker, Justin Fu, 2022, 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Fingerprint Policy Optimisation for Robust Reinforcement Learning

Shimon Whiteson, Michael A. Osborne, Supratik Paul, 2018, ICML.

Provably Convergent Off-Policy Actor-Critic with Function Approximation pdf

Shimon Whiteson, Bo Liu, Shangtong Zhang, 2019, ArXiv.

Universal Morphology Control via Contextual Modulation

Zheng Xiong, Shimon Whiteson, Jacob Beck, 2023, ICML.

Bounded Approximations for Linear Multi-Objective Planning Under Uncertainty

Shimon Whiteson, Mathijs de Weerdt, Frans A. Oliehoek, 2014, ICAPS.

Computing Convex Coverage Sets for Faster Multi-objective Coordination

Shimon Whiteson, Frans A. Oliehoek, Diederik M. Roijers, 2015, J. Artif. Intell. Res..

Transfer via inter-task mappings in policy search reinforcement learning

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2007, AAMAS '07.

Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving

A. Doucet, Maximilian Igl, J. Messias, 2022, CoRL.

Exploiting Best-Match Equations for Efficient Reinforcement Learning

Shimon Whiteson, Marco Wiering, Harm van Seijen, 2011, J. Mach. Learn. Res..

Learning Skills Diverse in Value-Relevant Features

Kristian Hartikainen, Jelena Luketina, Maximilian Igl, 2022, CoLLAs.

TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning

Tim Rocktäschel, Gregory Farquhar, Maximilian Igl, 2017, International Conference on Learning Representations.

Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning pdf

Shimon Whiteson, Jakob N. Foerster, Gregory Farquhar, 2019, NeurIPS.

The Waymo Open Sim Agents Challenge

Alex Kuefler, B. White, Drago Anguelov, 2023, NeurIPS.

Bayesian Exploration Networks

C. S. D. Witt, Shimon Whiteson, Matt Fellows, 2023, ArXiv.

Evolving Soccer Keepaway Players Through Task Decomposition

Risto Miikkulainen, Shimon Whiteson, Peter Stone, 2005, Machine Learning.

Evolving Keepaway Soccer Players through Task Decomposition

Risto Miikkulainen, Shimon Whiteson, Peter Stone, 2003, GECCO.

Comparing evolutionary and temporal difference methods in a reinforcement learning domain

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2006, GECCO.

Automatic feature selection in neuroevolution

Risto Miikkulainen, Shimon Whiteson, Kenneth O. Stanley, 2005, GECCO '05.

Rapidly exploring learning trees

Shimon Whiteson, Kyriacos Shiarlis, Joao Messias, 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

Using informative behavior to increase engagement in the tamer framework

Shimon Whiteson, Hayley Hung, W. Bradley Knox, 2013, AAMAS.

Multi-task evolutionary shaping without pre-specified representations

Shimon Whiteson, Matthijs Snel, M. Snel, 2010, GECCO '10.

Computing Convex Coverage Sets for Multi-objective Coordination Graphs

Shimon Whiteson, Frans A. Oliehoek, Diederik M. Roijers, 2013, ADT.

Multileave Gradient Descent for Fast Online Learning to Rank

M. de Rijke, Shimon Whiteson, Maarten de Rijke, 2016, WSDM.

A probabilistic method for inferring preferences from clicks

Katja Hofmann, M. de Rijke, Shimon Whiteson, 2011, CIKM '11.

Reusing historical interaction data for faster online learning to rank for IR

M. de Rijke, Anne Schuth, Katja Hofmann, 2013, WSDM.

Lerot: an online learning to rank framework

Katja Hofmann, M. de Rijke, Shimon Whiteson, 2013, LivingLab '13.

A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs

Shimon Whiteson, Jakob N. Foerster, Gregory Farquhar, 2019, ICML.

Contextual Bandits for Information Retrieval

Katja Hofmann, M. de Rijke, Shimon Whiteson, 2011 .

Fourier Policy Gradients

Matthew Fellows, Shimon Whiteson, Kamil Ciosek, 2018, ICML.

Reusing historical interaction data for faster online learning to rank for IR

M. de Rijke, Anne Schuth, Katja Hofmann, 2013, DIR.

Optimizing Base Rankers Using Clicks - A Case Study Using BM25

M. de Rijke, Floor Sietsma, Shimon Whiteson, 2014, ECIR.

Balancing exploration and exploitation in listwise and pairwise online learning to rank for information retrieval

M. de Rijke, K. Hofmann, Shimon Whiteson, 2012, Information Retrieval.

Balancing Exploration and Exploitation in Learning to Rank Online

Katja Hofmann, M. de Rijke, Shimon Whiteson, 2011, ECIR.

Hierarchical Imitation Learning for Stochastic Environments

B. White, K. Shiarlis, Maximilian Igl, 2023, 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Learning Retrospective Knowledge with Reverse Reinforcement Learning pdf

Shimon Whiteson, Shangtong Zhang, Vivek Veeriah, 2020, NeurIPS.

Automatic Feature Selection for Model-Based Reinforcement Learning in Factored MDPs

Shimon Whiteson, Mark Kroon, M. Kroon, 2009, 2009 International Conference on Machine Learning and Applications.

Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2007, AAAI.

On-line evolutionary computation for reinforcement learning in stochastic domains

Shimon Whiteson, Peter Stone, P. Stone, 2006, GECCO.

Transfer Learning for Policy Search Methods

Shimon Whiteson, Shimon Whiteson, 2006 .

Autonomous Agents and Multi-agent Systems Manuscript No. Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning

Matthew E. Taylor, P. Stone, Shimon Whiteson, 2022 .

Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem

M. de Rijke, R. Munos, M. Zoghi, 2013, ICML.

Facial feedback for reinforcement learning: a case study and offline analysis using the TAMER framework

Shimon Whiteson, Hamdi Dibeklioglu, Hayley Hung, 2020, Autonomous Agents and Multi-Agent Systems.

Exploiting Submodular Value Functions for Faster Dynamic Sensor Selection

F. Oliehoek, Shimon Whiteson, Yash Satsangi, 2015, AAAI.

JaxMARL: Multi-Agent RL Environments in JAX

Tim Rocktaschel, Timon Willi, C. S. D. Witt, 2023, ArXiv.

Bayesian Exploration Networks

C. S. D. Witt, Shimon Whiteson, Matt Fellows, 2023, ArXiv.

Why Target Networks Stabilise Temporal Difference Methods

Shimon Whiteson, Matt Fellows, Matthew Smith, 2023, ICML.

Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing

Vitaly Kurin, Maximilian Igl, Charlie Blake, 2021, NeurIPS.

Breaking the Deadly Triad with a Target Network

Hengshuai Yao, Shangtong Zhang, Shimon Whiteson, 2021, ICML.

Multi-Objective Decision Making

Diederik M. Roijers, Shimon Whiteson, 2017, Synthesis Lectures on Artificial Intelligence and Machine Learning.

Towards Personalised Gaming via Facial Expression Recognition

Chek Tien Tan, Paris Mavromoustakos Blom, T. Gevers, 2014, AIIDE.

UvA-DARE ( Digital Academic Repository ) Challenge Balancing for Personalised Game Spaces

George Viorel Visniuc, S. Whiteson, Guangliang Li, 2014 .

MAVEN: Multi-Agent Variational Exploration

Tabish Rashid, Mikayel Samvelyan, Shimon Whiteson, 2019, NeurIPS.

SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning

Mikayel Samvelyan, Shimon Whiteson, J. Foerster, 2022, NeurIPS.

Appendix for Regularized Softmax Deep Multi-Agent Q -Learning

Bei Peng, Tabish Rashid, L. Pan, 2021 .

Approximate solutions for factored Dec-POMDPs with many agents

F. Oliehoek, M. Spaan, Shimon Whiteson, 2013, AAMAS.

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control pdf

Shimon Whiteson, Tim Rocktäschel, Vitaly Kurin, 2020, ICLR.

Discovering Temporally-Aware Reinforcement Learning Algorithms

Shimon Whiteson, Robert Tjarko Lange, Chris Lu, 2024, ArXiv.