Learning to Combat Compounding-Error in Model-Based Reinforcement Learning

24 December 2019

Papers citing "Learning to Combat Compounding-Error in Model-Based Reinforcement Learning"

10 / 10 papers shown

Title
MADiff: Offline Multi-agent Learning with Diffusion Models Zhengbang Zhu Minghuan Liu Liyuan Mao Bingyi Kang Minkai Xu Yong Yu Stefano Ermon Weinan Zhang DiffM OffRL 90 34 0 03 Jan 2025
Backward Imitation and Forward Reinforcement Learning via Bi-directional Model Rollouts Yuxin Pan Fangzhen Lin OffRL 25 3 0 04 Aug 2022
Deep Surrogate Assisted Generation of Environments Varun Bhatt Bryon Tjanaka Matthew C. Fontaine Stefanos Nikolaidis 56 35 0 09 Jun 2022
Mingling Foresight with Imagination: Model-Based Cooperative Multi-Agent Reinforcement Learning Zhiwei Xu Dapeng Li Bin Zhang Yuan Zhan Yunru Bai Guoliang Fan OffRL 27 7 0 20 Apr 2022
Revisiting Model-based Value Expansion Daniel Palenicek M. Lutter Jan Peters 27 2 0 28 Mar 2022
Investigating Compounding Prediction Errors in Learned Dynamics Models Nathan Lambert K. Pister Roberto Calandra AI4CE 22 27 0 17 Mar 2022
Explaining Off-Policy Actor-Critic From A Bias-Variance Perspective Ting-Han Fan Peter J. Ramadge CML FAtt OffRL 21 2 0 06 Oct 2021
Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning Nathan Lambert Albert Wilcox Howard Zhang K. Pister Roberto Calandra 25 33 0 16 Dec 2020
Model-based Policy Optimization with Unsupervised Model Adaptation Jian Shen Han Zhao Weinan Zhang Yong Yu 32 27 0 19 Oct 2020
Selective Dyna-style Planning Under Limited Model Capacity Zaheer Abbas Samuel Sokota Erin J. Talvitie Martha White 27 32 0 05 Jul 2020