Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

2 May 2018

Papers citing "Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review"

33 / 133 papers shown

Title
Skill Discovery of Coordination in Multi-agent Reinforcement Learning Shuncheng He Jianzhun Shao Xiangyang Ji 26 7 0 07 Jun 2020
Acme: A Research Framework for Distributed Reinforcement Learning Matthew W. Hoffman Bobak Shahriari John Aslanides Gabriel Barth-Maron Nikola Momchev ... Srivatsan Srinivasan A. Cowie Ziyun Wang Bilal Piot Nando de Freitas 65 225 0 01 Jun 2020
Self-Paced Deep Reinforcement Learning Pascal Klink Carlo DÉramo Jan Peters Joni Pajarinen ODL 38 54 0 24 Apr 2020
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning Wenhao Li Bo Jin Xiangfeng Wang Junchi Yan H. Zha 25 21 0 17 Apr 2020
Whence the Expected Free Energy? Beren Millidge Alexander Tschantz Christopher L. Buckley 20 69 0 17 Apr 2020
Leverage the Average: an Analysis of KL Regularization in RL Nino Vieillard Tadashi Kozuno B. Scherrer Olivier Pietquin Rémi Munos M. Geist 25 42 0 31 Mar 2020
Reinforcement Learning through Active Inference Alexander Tschantz Beren Millidge A. Seth Christopher L. Buckley AI4CE 26 69 0 28 Feb 2020
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement Benjamin Eysenbach Xinyang Geng Sergey Levine Ruslan Salakhutdinov OffRL 18 86 0 25 Feb 2020
Making Sense of Reinforcement Learning and Probabilistic Inference Brendan O'Donoghue Ian Osband Catalin Ionescu OffRL 27 48 0 03 Jan 2020
Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans Nachiket Deo Mohan M. Trivedi 24 149 0 03 Jan 2020
Learning Data Manipulation for Augmentation and Weighting Zhiting Hu Bowen Tan Ruslan Salakhutdinov Tom Michael Mitchell Eric Xing 29 116 0 28 Oct 2019
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control H. F. Song A. Abdolmaleki Jost Tobias Springenberg Aidan Clark Hubert Soyer ... Dhruva Tirumala N. Heess Dan Belov Martin Riedmiller M. Botvinick 37 121 0 26 Sep 2019
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment Felix Leibfried Sergio Pascual-Diaz Jordi Grau-Moya 25 27 0 26 Jul 2019
An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems Heinke Hihn Sebastian Gottwald Daniel A. Braun 24 16 0 26 Jul 2019
Deep Active Inference as Variational Policy Gradients Beren Millidge BDL 32 103 0 08 Jul 2019
Variational Inference MPC for Bayesian Model-based Reinforcement Learning Masashi Okada T. Taniguchi 38 73 0 08 Jul 2019
Integration of Imitation Learning using GAIL and Reinforcement Learning using Task-achievement Rewards via Probabilistic Graphical Model Akira Kinose T. Taniguchi 30 20 0 03 Jul 2019
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model Alex X. Lee Anusha Nagabandi Pieter Abbeel Sergey Levine OffRL BDL 30 372 0 01 Jul 2019
Training an Interactive Helper Mark P. Woodward Chelsea Finn Karol Hausman 27 1 0 24 Jun 2019
Better transfer learning with inferred successor maps T. Madarász 19 21 0 18 Jun 2019
A Regularized Opponent Model with Maximum Entropy Objective Zheng Tian Ying Wen Zhichen Gong Faiz Punakkath Shihao Zou Jun Wang 30 31 0 17 May 2019
Consequential Ranking Algorithms and Long-term Welfare Behzad Tabibian Vicencc Gómez A. De Bernhard Schölkopf Manuel Gomez Rodriguez 12 6 0 13 May 2019
Bayesian Gaussian mixture model for robotic policy imitation Emmanuel Pignat Sylvain Calinon 23 46 0 24 Apr 2019
End-to-End Robotic Reinforcement Learning without Reward Engineering Avi Singh Larry Yang Kristian Hartikainen Chelsea Finn Sergey Levine SSL OffRL 46 266 0 16 Apr 2019
Modelling Bounded Rationality in Multi-Agent Interactions by Generalized Recursive Reasoning Ying Wen Yaodong Yang Rui Luo Jun Wang LRM 29 52 0 26 Jan 2019
Deconfounding Reinforcement Learning in Observational Settings Chaochao Lu Bernhard Schölkopf José Miguel Hernández-Lobato CML OOD 30 73 0 26 Dec 2018
A new approach to learning in Dynamic Bayesian Networks (DBNs) E. Benhamou J. Atif R. Laraki 14 7 0 21 Dec 2018
Connecting the Dots Between MLE and RL for Sequence Prediction Bowen Tan Zhiting Hu Zichao Yang Ruslan Salakhutdinov Eric Xing 28 24 0 24 Nov 2018
VIREL: A Variational Inference Framework for Reinforcement Learning M. Fellows Anuj Mahajan Tim G. J. Rudner Shimon Whiteson DRL 35 54 0 03 Nov 2018
Variational Inference with Tail-adaptive f-Divergence Dilin Wang Hao Liu Qiang Liu 27 55 0 29 Oct 2018
Bayesian Transfer Reinforcement Learning with Prior Knowledge Rules Michalis K. Titsias Sotirios Nikoloutsopoulos BDL OffRL 13 3 0 30 Sep 2018
Boosting Trust Region Policy Optimization by Normalizing Flows Policy Yunhao Tang Shipra Agrawal TPM 25 29 0 27 Sep 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017