Provably Efficient Reward Transfer in Reinforcement Learning with Discrete Markov Decision Processes

arXiv:2503.13414 · cs.LG, cs.AI · Submitted 2025-03-17 · Read on arXiv

cs.LG, cs.AI

Submitted: 2025-03-17

Updated: 2025-10-22

Terminology

• Reward Function — 36× in this paper · explained in 2 episodes
• Reinforcement Learning — 33× in this paper · explained in 4 episodes
• Pruning — 25× in this paper · explained in 4 episodes
• Adaptation — 23× in this paper · explained in 1 episode
• Lower Bound — 17× in this paper
• Reward Adaptation — 17× in this paper
• Transfer Learning — 13× in this paper · explained in 10 episodes
• Action Space — 9× in this paper · explained in 1 episode
• Q-learning — 8× in this paper · explained in 3 episodes
• Sample Complexity — 8× in this paper · explained in 15 episodes
• Upper Bound — 7× in this paper
• Generalization — 6× in this paper · explained in 13 episodes
• Deep Reinforcement Learning — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Generalizability — 2× in this paper · explained in 6 episodes
• Regret — 2× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 2× in this paper · explained in 25 episodes
• Sample Efficiency — 2× in this paper · explained in 4 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Continual Learning — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Multi-Task Reinforcement Learning — 1× in this paper
• Robustness — 1× in this paper · explained in 5 episodes
• Soft Q Bounding — 1× in this paper
• Successor Feature Q-Learning — 1× in this paper
• Temporal Abstraction — 1× in this paper · explained in 2 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes

Sources

• Boosting Soft Q-Learning by Bounding
• Bellman operator convergence enhancements in reinforcement learning algorithms
• Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities

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