Reinforcement learning

Publication

Optimistic posterior sampling for reinforcement learning with few samples and tight guarantees

Daniil Tiapkin *, Denis Belomestny *, Daniele Calandriello, Eric Moulines *, Alexey Naumov *, Remi Munos, Mark Rowland, Pierre Menard *, Michal Valko

NeurIPS

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COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation

Jongmin Lee *, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim *, Arthur Guez

ICLR

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Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality

Tom Zahavy, Feryal Behbahani, Yannick Schroecker, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Baveja

European Workshop on Reinforcement Learning (EWRL)

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Publication

On Reward Binarisation and Bayesian Agents

Elliot Catt, Marcus Hutter, Joel Veness

European Workshop on Reinforcement Learning (EWRL)

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Publication

Optimizing Industrial Cooling Systems with Hierarchical Reinforcement Learning

William Wong *, Praneet Dutta, Jerry Luo, Octavian Voicu, Yuri Chervonyi, Cosmin Paduraru

arXiv

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From Motor Control to Team Play in Simulated Humanoid Football

Siqi Liu, Guy Lever, Zhe Wang, Ali Eslami, Daniel Hennes, Wojtek Czarnecki, Yuval Tassa, Abbas Abdolmaleki, Noah Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan Tracey, Karl Tuyls

Science Robotics

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Reinforcement Learning with Information Theoretic Actuation

Elliot Catt, Marcus Hutter, Joel Veness

arXiv

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Publication

Semi-analytical Industrial Cooling System Model for Reinforcement Learning

Yuri Chervonyi, Praneet Dutta, Piotr Trochim *, Octavian Voicu, Cosmin Paduraru, Crystal Qian, Emre Karagozler, Jared Quincy Davis, Richard Chippendale *, Gautam Bajaj *, Sims Witherspoon, Jerry Luo

arXiv

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Publication

Generalised Policy Improvement with Geometric Policy Composition

Shantanu Thakoor, Mark Rowland, Diana Borsa, Will Dabney, Remi Munos, Andre Barreto

ICML

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Publication

From Dirichlet to Rubin: Optimistic exploration in RL without bonuses

Daniil Tiapkin *, Denis Belomestny *, Éric Moulines *, Alexey Naumov *, Sergey Samsonov *, Yunhao Tang, Michal Valko, Pierre Menard *

ICML

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Publication

Expressing Non-Markov Reward to a Markov Agent

David Abel, Andre Barreto, Michael Bowling, Will Dabney, Steven Hansen, Anna Harutyunyan, Mark Ho *, Ramana Kumar, Michael Littman *, Doina Precup, Satinder Singh *

RLDM

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Publication

A Simple Approach for State-Action Abstraction\\using a Learned MDP Homomorphism

Augustine Mavor-Parker *, Andrea Banino, Lewis Griffin *, Caswell Barry *

RLDM

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Publication

Uniqueness and Complexity of Inverse MDP Models

Marcus Hutter

arXiv

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Publication

Active offline policy selection

Yutian Chen, Ksenia Konyushkova, Tom Paine, Caglar Gulcehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas

NeurIPS

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Publication

An adaptive and efficient multi-goal exploration

Jean Tarbouriech *, Omar Darwiche Domingues *, Pierre Ménard *, Matteo Pirotta *, Michal Valko, Alessandro Lazaric *

AISTATS

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Publication

Marginalized operators for off-policy reinforcement learning

Yunhao Tang *, Mark Rowland, Remi Munos, Michal Valko

AISTATS

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Your Policy Regularizer is Secretly an Adversary

Rob Brekelmans *, Tim Genewein, Jordi Grau, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro Ortega

arXiv

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Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO

Paul Muller, Mark Rowland, Romuald Elie, Julien Perolat, Karl Tuyls, G Piliouras *, Olivier Pietquin, M Lauriere *, Raphael Marinier *

AAMAS

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Publication

Online Apprenticeship Learning

Lior Shani *, Tom Zahavy, Shie Mannor *

AAAI

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Publication

Chaining Value Functions for Off-Policy Learning

Simon Schmitt, John Shawe-Taylor *, Hado van Hasselt

AAAI

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Publication

Reward-Punishment Symmetric Universal Intelligence

Marcus Hutter, Samuel Allen Alexander *

arXiv

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Publication

Assessing Human Interaction in Virtual Reality with Continually Learning Prediction Agents Based on Reinforcement Learning Algorithms: A Pilot Study

Dylan Brenneis, Andrew Butcher, Elnaz Davoodi, Mike Johanson, Leslie Acker, Matt Botvinick, Joseph Modayil, Adam White, Patrick Pilarski, Adam S. R. Parker *

arXiv

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Publication

Model-Value Self-Inconsistency as a Signal for Epistemic Uncertainty

Angelos Filos, Eszter Vértes, Zita Marinho, Greg Farquhar, Diana Borsa, Abe Friesen, Feryal Behbahani, Tom Schaul, Andre Barreto, Simon Osindero

ICML

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On the Expressivity of Markov Reward

David Abel, Doina Precup, Anna Harutyunyan, Mark Ho *, Michael Littman *, Will Dabney, Satinder Baveja

NeurIPS

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Publication

The Difficulty of Passive Learning in Deep Reinforcement Learning

Georg Ostrovski, P Castro *, Will Dabney

NeurIPS

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Publications

Reinforcement learning