We show in this paper that we can reuse prior data to extend new skills simply through model-free reinforcement learning via dynamic programming.
Nov 14, 2020 · "**Chaining Behaviors from Data with Model-Free Reinforcement Learning** Avi Singh (UC Berkeley)*; Albert Yu (UC Berkeley); Jonathan Yang ...
Chaining Behaviors from Data with Model-Free Reinforcement Learning · Avi Singh, Albert Yu, +3 authors. S. Levine · Published in Conference on Robot Learning 2020 ...
Workshop: Deep Reinforcement Learning. Poster: Chaining Behaviors from Data with Model-Free Reinforcement Learning. Abstract: It appears you are a search ...
Workshop: Offline Reinforcement Learning. Contributed Talk 2: Chaining Behaviors from Data with Model-Free Reinforcement Learning. Avi Singh. Abstract: It ...
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Nov 7, 2017 · In Reinforcement Learning, the terms "model-based" and "model-free" do not refer to the use of a neural network or other statistical learning ...
Nov 23, 2023 · Model-based RL often offers greater data efficiency, as it can use models to evaluate many possible behaviors before choosing one to enact.
May 15, 2016 · The model-based reinforcement learning tries to study the environment while model-free reinforcement learning does not. The model here means ...
Jan 14, 2024 · In this article we will first get a basic overview of RL, then we will discuss the difference between model-based and model-free algorithms in detail.
Model-free reinforcement learning (RL) has been proven to be a powerful, general tool for learning complex behaviors. However, its sample efficiency is ...