Jun 26, 2020 · In this paper, we propose a novel offline RL algorithm to learn policies from data using a form of critic-regularized regression (CRR).
In this paper, we propose a novel offline RL algorithm to learn policies from data using a form of critic-regularized regression (CRR). We find that. CRR ...
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This paper proposes a simple yet effective method by filtering off-distribution actions in the domain of offline RL.
In this paper, we propose a novel offline RL algorithm to learn policies from data using a form of critic-regularized regression (CRR).
Dec 17, 2022 · A simple but powerful algorithm for offline reinforcement learning, which can be seen as a combination of behavior cloning and Q-learning, ...
In this paper, we propose a novel offline RL algorithm to learn policies from data using a form of critic-regularized regression (CRR). We find that CRR ...
In this paper, we propose a novel offline RL algorithm to learn policies from data using a form of critic-regularized regression (CRR). CRR essentially reduces ...
CRR (Critic Regularized Regression). CRR is another offline RL algorithm based on Q-learning that can learn from an offline experience replay.
This repo implements 3 different algorithms: Conservative Q-learning (CQL); Critic Regularized Regression (CRR); Behavioural Cloning adopted from acme. Examples.
Jun 26, 2020 · This paper proposes a novel offline RL algorithm to learn policies from data using a form of critic-regularized regression (CRR), ...