Reinforcement learning

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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Publication

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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Publication

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

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

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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Publication

Importance of Representation Learning for Off-Policy Fitted Q-Evaluation

Xian Wu *, Nevena Lazic, Dong Yin, Cosmin Paduraru

NeurIPS Workshop

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Publication

Towards mental time travel: a hierarchical memory for reinforcement learning agents

Andrew Lampinen, Stephanie Chan, Andrea Banino, Felix Hill

NeurIPS

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Publication

When should agents explore?

Tom Schaul, Georg Ostrovski, Diana Borsa, David Szepesvari, Miruna Pislar

ICLR

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Publication

Temporally Abstract Partial Models

Khimya Khetarpal *, Zafarali Ahmed, Gheorghe Comanici, Doina Precup

NeurIPS

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Publication

Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning

Justin Fu, Andrea Tacchetti, Julien Perolat, Yoram Bachrach

The Journal of Artificial Intelligence Research

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Publication

Improved Chinese Sentence Segmentation with Reinforcement Learning

Srivatsan Srinivasan, Chris Dyer

ACL

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Publication

Revisiting Peng's Q(λ) for modern reinforcement learning

Tadashi Kozuno *, Yunhao Tang *, Mark Rowland, Remi Munos, Steven Kapturowski, Will Dabney, Michal Valko, David Abel

ICML

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Publication

Taylor expansions of discount factors

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

ICML

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Publication

Kernel-based reinforcement Learning: A finite-time analysis

O Domingues *, Pierre Menard *, Matteo Pirotta *, Emilie Kaufmann *, Michal Valko

ICML

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Publication

PsiPhi: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning

Angelos Filos, Clare Lyle *, Yarin Gal *, Sergey Levine *, Natasha Jaques *, Greg Farquhar

ICML

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Publication

Unifying gradient estimators for meta-reinforcement learning via off-policy evaluation

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

NeurIPS

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Publication

Learning in two-player zero-sum partially observable Markov games with perfect recall

Tadashi Kozuno *, Pierre Ménard *, Remi Munos, Michal Valko

NeurIPS

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Publication

Representation Matters: Improving Observations and Exploration for Robotics

Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, Irina Higgins, Ankush Gupta, Malcolm Reynolds, Denis Teplyashin, Martin Riedmiller, Roland Hafner, Tejas Kulkarni *

IEEE International Conference on Robotics and Automation

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Publication

Return-based Scaling: Yet Another Normalisation Trick for Deep RL

Tom Schaul, Georg Ostrovski, Iurii Kemaev, Diana Borsa

arXiv

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Publication

Stochastic shortest path: minimax, parameter-free and towards horizon-free regret

Jean Tarbouriech *, Runlong Zhou *, Simon S. Du *, Matteo Pirotta *, Michal Valko, Alessandro Lazaric *

NeurIPS

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Publications

Reinforcement learning