Jun 16, 2021 · We investigate how to improve the performance of offline RL algorithms, its robustness to the quality of offline data, as well as its ...
Offline Model-Based RL with Adaptive Behavioral Priors (MABE) ... leveraging the learned dynamics model and transferring of behavioral priors across datasets,.
Jun 16, 2021 · We investigate how to improve the performance of offline RL algorithms, its robustness to the quality of offline data, as well as its ...
Jun 16, 2021 · This work introduces Offline Model-based RL with Adaptive Behavioral Priors (MABE), a algorithm based on the finding that dynamics models ...
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3) MABE has the unique capability of utilizing behavioral priors and dynamics models from different domains, thereby enabling effective cross-domain transfer.
arXiv, 2021. Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL [website]. Catherine Cang, Aravind Rajeswaran ...
Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL Catherine Cang, Aravind Rajeswaran, Pieter Abbeel, Michael ...
Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL ... improve the performance and generalization of offline RL ...
Offline Reinforcement Learning (RL) aims to extract near-optimal policies from imperfect offline data without additional environment interactions.
Feb 16, 2022 · - Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL [website]. Catherine Cang, Aravind ...