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For SALE: State-Action Representation Learning for Deep Reinforcement Learning

initial_h 2024-08-06 01:17 阅读:188 评论:0 推荐:0 编辑

Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning

initial_h 2024-06-11 11:15 阅读:144 评论:0 推荐:0 编辑

Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods

initial_h 2024-05-23 13:38 阅读:507 评论:0 推荐:0 编辑

RETROFORMER: RETROSPECTIVE LARGE LANGUAGE AGENTS WITH POLICY GRADIENT OPTIMIZATION

initial_h 2024-05-13 23:56 阅读:147 评论:0 推荐:0 编辑

REACT: SYNERGIZING REASONING AND ACTING IN LANGUAGE MODELS

initial_h 2024-05-04 23:05 阅读:324 评论:0 推荐:0 编辑

Reflexion: Language Agents with Verbal Reinforcement Learning

initial_h 2024-04-30 11:24 阅读:479 评论:0 推荐:0 编辑

Large Language Models Are Semi-Parametric Reinforcement Learning Agents

initial_h 2024-04-24 13:48 阅读:98 评论:0 推荐:0 编辑

Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

initial_h 2024-03-04 10:13 阅读:216 评论:0 推荐:0 编辑

Improved Soft Actor-Critic: Mixing Prioritized Off-Policy Samples with On-Policy Experience

initial_h 2024-03-01 03:22 阅读:40 评论:0 推荐:0 编辑

State Distribution-aware Sampling for Deep Q-learning

initial_h 2024-02-24 01:04 阅读:42 评论:0 推荐:0 编辑

Large Batch Experience Replay

initial_h 2024-02-17 00:50 阅读:29 评论:0 推荐:0 编辑

Prioritized Experience Replay

initial_h 2024-02-14 08:29 阅读:76 评论:0 推荐:0 编辑

Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update

initial_h 2024-02-11 02:46 阅读:29 评论:0 推荐:0 编辑

Experience Replay with Likelihood-free Importance Weights

initial_h 2023-08-13 23:20 阅读:58 评论:0 推荐:0 编辑

Striving for Simplicity and Performance in Off-Policy DRL: Output Normalization and Non-Uniform Sampling

initial_h 2023-08-12 08:00 阅读:46 评论:0 推荐:0 编辑