Summary of Statistical Guarantees For Lifelong Reinforcement Learning Using Pac-bayesian Theory, by Zhi Zhang et al.
Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayesian Theory
by Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla
First submitted to arxiv on: 1 Nov 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes EPIC (Empirical PAC-Bayes that Improves Continuously), an algorithm for lifelong reinforcement learning. Lifelong RL models the “life” of an agent as a stream of tasks drawn from a task distribution, enabling extension to more realistic and dynamic settings. EPIC learns a shared policy distribution, referred to as the world policy, allowing rapid adaptation to new tasks while retaining valuable knowledge from previous experiences. Theoretical analysis establishes a relationship between generalization performance and preserved prior tasks in memory, and derives sample complexity in terms of RL regret. Experimental results demonstrate that EPIC significantly outperforms existing methods in lifelong RL, offering both theoretical guarantees and practical efficacy through the world policy. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper talks about how artificial intelligence can learn new things without forgetting old ones. It’s called “lifelong learning”. The researchers created a new way for this to happen, which they call EPIC. EPIC helps machines remember what they learned from one task and apply it to other tasks. This is important because it makes the machine better at solving problems over time. The paper shows that EPIC works well in different situations and is better than previous ways of doing lifelong learning. |
Keywords
» Artificial intelligence » Generalization » Reinforcement learning
