Maximum a Posteriori Policy Optimisation

14 June 2018

A. Abdolmaleki

Jost Tobias Springenberg

Martin Riedmiller

Papers citing "Maximum a Posteriori Policy Optimisation"

50 / 136 papers shown

Title
Forgetting and Imbalance in Robot Lifelong Learning with Off-policy Data Wenxuan Zhou Steven Bohez Jan Humplik A. Abdolmaleki Dushyant Rao Markus Wulfmeier Tuomas Haarnoja N. Heess OffRL 32 6 0 12 Apr 2022
Monte Carlo Tree Search based Hybrid Optimization of Variational Quantum Circuits Jiahao Yao Haoya Li Marin Bukov Lin Lin Lexing Ying 16 15 0 30 Mar 2022
DARA: Dynamics-Aware Reward Augmentation in Offline Reinforcement Learning Jinxin Liu Hongyin Zhang Donglin Wang OffRL 24 32 0 13 Mar 2022
Robot Learning of Mobile Manipulation with Reachability Behavior Priors Snehal Jauhri Jan Peters Georgia Chalvatzaki 18 45 0 08 Mar 2022
Learning Robust Real-Time Cultural Transmission without Human Data Cultural General Intelligence Team Avishkar Bhoopchand Bethanie Brownfield Adrian Collister Agustin Dal Lago ... Alex Platonov Evan Senter Sukhdeep Singh Alexander Zacherl Lei M. Zhang VLM 42 11 0 01 Mar 2022
Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics Honghu Xue Benedikt Hein M. Bakr Georg Schildbach Bengt Abel Elmar Rueckert 16 15 0 23 Feb 2022
Retrieval-Augmented Reinforcement Learning Anirudh Goyal A. Friesen Andrea Banino T. Weber Nan Rosemary Ke ... Michal Valko Simon Osindero Timothy Lillicrap N. Heess Charles Blundell OffRL 32 53 0 17 Feb 2022
NeuPL: Neural Population Learning Siqi Liu Luke Marris Daniel Hennes J. Merel N. Heess T. Graepel 30 17 0 15 Feb 2022
Bingham Policy Parameterization for 3D Rotations in Reinforcement Learning Stephen James Pieter Abbeel 32 9 0 08 Feb 2022
Conservative Distributional Reinforcement Learning with Safety Constraints Hengrui Zhang Youfang Lin Sheng Han Shuo Wang Kai Lv OffRL 21 5 0 18 Jan 2022
Towards an Understanding of Default Policies in Multitask Policy Optimization Theodore H. Moskovitz Michael Arbel Jack Parker-Holder Aldo Pacchiano 22 9 0 04 Nov 2021
Self-Consistent Models and Values Roy Miles Kate Baumli Zita Marinho Angelos Filos Matteo Hessel Hado van Hasselt David Silver 38 8 0 25 Oct 2021
Evaluating model-based planning and planner amortization for continuous control Arunkumar Byravan Leonard Hasenclever Piotr Trochim M. Berk Mirza Alessandro Davide Ialongo ... Jost Tobias Springenberg A. Abdolmaleki N. Heess J. Merel Martin Riedmiller 55 17 0 07 Oct 2021
Dropout Q-Functions for Doubly Efficient Reinforcement Learning Takuya Hiraoka Takahisa Imagawa Taisei Hashimoto Takashi Onishi Yoshimasa Tsuruoka 11 104 0 05 Oct 2021
Learning Dynamics Models for Model Predictive Agents M. Lutter Leonard Hasenclever Arunkumar Byravan Gabriel Dulac-Arnold Piotr Trochim N. Heess J. Merel Yuval Tassa AI4CE 57 26 0 29 Sep 2021
Dual Behavior Regularized Reinforcement Learning Chapman Siu Jason M. Traish R. Xu OffRL 15 1 0 19 Sep 2021
Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Exploration Oliver Groth Markus Wulfmeier Giulia Vezzani Vibhavari Dasagi Tim Hertweck Roland Hafner N. Heess Martin Riedmiller LRM 41 20 0 17 Sep 2021
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning Tianhe Yu Aviral Kumar Yevgen Chebotar Karol Hausman Sergey Levine Chelsea Finn OffRL 35 77 0 16 Sep 2021
Bootstrapped Meta-Learning Sebastian Flennerhag Yannick Schroecker Tom Zahavy Hado van Hasselt David Silver Satinder Singh 38 58 0 09 Sep 2021
Implicitly Regularized RL with Implicit Q-Values Nino Vieillard Marcin Andrychowicz Anton Raichuk Olivier Pietquin M. Geist OffRL 24 9 0 16 Aug 2021
Goal-Conditioned Reinforcement Learning with Imagined Subgoals Elliot Chane-Sane Cordelia Schmid Ivan Laptev 19 140 0 01 Jul 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 20 7 0 30 Jun 2021
Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL Catherine Cang Aravind Rajeswaran Pieter Abbeel Michael Laskin OffRL 19 29 0 16 Jun 2021
Simplifying Deep Reinforcement Learning via Self-Supervision Daochen Zha Kwei-Herng Lai Kaixiong Zhou Xia Hu SSL 28 15 0 10 Jun 2021
Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint M. Geist Julien Pérolat Mathieu Laurière Romuald Elie Sarah Perrin Olivier Bachem Rémi Munos Olivier Pietquin 37 62 0 07 Jun 2021
From Motor Control to Team Play in Simulated Humanoid Football Siqi Liu Guy Lever Zhe Wang J. Merel S. M. Ali Eslami ... Tuomas Haarnoja Brendan D. Tracey K. Tuyls T. Graepel N. Heess 31 129 0 25 May 2021
Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation Emilio Parisotto Ruslan Salakhutdinov 42 44 0 04 Apr 2021
Near Optimal Policy Optimization via REPS Aldo Pacchiano Jonathan Lee Peter L. Bartlett Ofir Nachum 18 3 0 17 Mar 2021
Maximum Entropy RL (Provably) Solves Some Robust RL Problems Benjamin Eysenbach Sergey Levine OOD 38 175 0 10 Mar 2021
Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing Axel Brunnbauer Luigi Berducci Andreas Brandstätter Mathias Lechner Ramin Hasani Daniela Rus Radu Grosu LM&Ro 38 37 0 08 Mar 2021
Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction Hongyao Tang Jianye Hao Guangyong Chen Pengfei Chen Cheng Chen Yaodong Yang Lu Zhang Wulong Liu Zhaopeng Meng OffRL 32 4 0 03 Mar 2021
Optimization Issues in KL-Constrained Approximate Policy Iteration N. Lazić Botao Hao Yasin Abbasi-Yadkori Dale Schuurmans Csaba Szepesvári 19 10 0 11 Feb 2021
Approximately Solving Mean Field Games via Entropy-Regularized Deep Reinforcement Learning Kai Cui Heinz Koeppl 64 91 0 02 Feb 2021
Decoupled Exploration and Exploitation Policies for Sample-Efficient Reinforcement Learning William F. Whitney Michael Bloesch Jost Tobias Springenberg A. Abdolmaleki Kyunghyun Cho Martin Riedmiller OffRL 29 13 0 23 Jan 2021
Differentiable Trust Region Layers for Deep Reinforcement Learning Fabian Otto P. Becker Ngo Anh Vien Hanna Ziesche Gerhard Neumann OffRL 36 19 0 22 Jan 2021
Grounding Artificial Intelligence in the Origins of Human Behavior Eleni Nisioti Clément Moulin-Frier AI4CE 39 5 0 15 Dec 2020
Behavior Priors for Efficient Reinforcement Learning Dhruva Tirumala Alexandre Galashov Hyeonwoo Noh Leonard Hasenclever Razvan Pascanu ... Guillaume Desjardins Wojciech M. Czarnecki Arun Ahuja Yee Whye Teh N. Heess 37 39 0 27 Oct 2020
Logistic Q-Learning Joan Bas-Serrano Sebastian Curi Andreas Krause Gergely Neu 9 40 0 21 Oct 2020
Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification D. Mankowitz D. A. Calian Rae Jeong Cosmin Paduraru N. Heess Sumanth Dathathri Martin Riedmiller Timothy A. Mann 24 11 0 20 Oct 2020
Learning Dexterous Manipulation from Suboptimal Experts Rae Jeong Jost Tobias Springenberg Jackie Kay Daniel Zheng Yuxiang Zhou Alexandre Galashov N. Heess F. Nori OffRL 10 36 0 16 Oct 2020
Data-efficient Hindsight Off-policy Option Learning Markus Wulfmeier Dushyant Rao Roland Hafner Thomas Lampe A. Abdolmaleki ... Michael Neunert Dhruva Tirumala Noah Y. Siegel N. Heess Martin Riedmiller OffRL 23 47 0 30 Jul 2020
Monte-Carlo Tree Search as Regularized Policy Optimization Jean-Bastien Grill Florent Altché Yunhao Tang Thomas Hubert Michal Valko Ioannis Antonoglou Rémi Munos 19 73 0 24 Jul 2020
Control as Hybrid Inference Alexander Tschantz Beren Millidge A. Seth Christopher L. Buckley 19 9 0 11 Jul 2020
Critic Regularized Regression Ziyun Wang Alexander Novikov Konrad Zolna Jost Tobias Springenberg Scott E. Reed ... Noah Y. Siegel J. Merel Çağlar Gülçehre N. Heess Nando de Freitas OffRL 36 317 0 26 Jun 2020
AWAC: Accelerating Online Reinforcement Learning with Offline Datasets Ashvin Nair Abhishek Gupta Murtaza Dalal Sergey Levine OffRL OnRL 16 585 0 16 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 25 82 0 15 Jun 2020
What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study Marcin Andrychowicz Anton Raichuk Piotr Stańczyk Manu Orsini Sertan Girgin ... M. Geist Olivier Pietquin Marcin Michalski Sylvain Gelly Olivier Bachem OffRL 31 213 0 10 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 54 225 0 01 Jun 2020
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals Henry Charlesworth Giovanni Montana OffRL 16 24 0 01 Jun 2020
A Distributional View on Multi-Objective Policy Optimization A. Abdolmaleki Sandy H. Huang Leonard Hasenclever Michael Neunert H. F. Song Martina Zambelli M. Martins N. Heess R. Hadsell Martin Riedmiller 21 74 0 15 May 2020