Deep reinforcement learning

Publication

Scaling Goal-based Exploration via Pruning Proto-goals

Akhil Bagaria *, Ray Jiang, Ramana Kumar, Tom Schaul

arXiv

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Equivariant MuZero

Andreea Deac *, Theophane Weber, George Papamakarios

arXiv

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Exploration via Epistemic Value Estimation

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

AAAI

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Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition

Peter Sunehag, Joel Leibo, Sasha Vezhnevets, Igor Mordatch *, Edgar Duéñez-Guzmán

AAMAS

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An empirical study of implicit regularization in deep offline RL

Caglar Gulcehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Matt Hoffman, Mehrdad Farajtabar, Razvan Pascanu, Arnaud Doucet

Transactions on Machine Learning Research (TMLR)

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Continuous Neural Algorithmic Planners

Yu He *, Petar Veličković, Pietro Liò *, Andreea-Ioana Deac

LoG

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BLaDE: Robust Exploration via Diffusion Models

Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Shantanu Thakoor

Deep RL Workshop NeurIPS

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Large-Scale Retrieval for Reinforcement Learning

Peter Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Theophane Weber, Timothy Lillicrap

NeurIPS

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Semantic Exploration from Language Abstractions and Pretrained Representations

Allison Tam, Neil Rabinowitz, Andrew Lampinen, Nick Roy, Stephanie Chan, DJ Strouse, Jane Wang, Andrea Banino, Felix Hill

NeurIPS

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Curiosity in hindsight

Dan Jarrett, Corentin Tallec, Florent Altché, Thomas Mesnard, Remi Munos, Michal Valko

Deep RL Workshop NeurIPS

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Palm up: Playing in the Latent Manifold for Unsupervised Pretraining

Hao Liu *, Tom Zahavy, Vlad Mnih, Satinder Baveja

NeurIPS

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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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Probing Transfer in Deep Reinforcement Learning without Task Engineering

Andrei Rusu, Sebastian Flennerhag, Dushyant Rao, Razvan Pascanu, Raia Hadsell

CoLLAs

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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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Generalised Policy Improvement with Geometric Policy Composition

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

ICML

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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

BYOL-Explore: Exploration by bootstrapped prediction

Daniel Guo, Shantanu Thakoor, Miruna Pislar, Corentin Tallec, Florent Altché, Bernardo Avila Pires, Yunhao Tang, Alaa Saade, Jean-bastien Grill, Michal Valko, Mohammad Gheshlaghi Azar, Bilal Piot, Remi Munos, Daniele Calandriello

NeurIPS

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Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games

Siqi Liu, Marc Lanctot, Luke Marris, Nicolas Heess, David Silver

ICML

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Publication

Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning

Mike Johanson, Edward Hughes, Finbarr Timbers, Joel Leibo

arXiv

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