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2009 NIPS NeurIPS 2009

Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining

Abstract

We introduce skill chaining, a skill discovery method for reinforcement learning agents in continuous domains, that builds chains of skills leading to an end-of-task reward. We demonstrate experimentally that it creates skills that result in performance benefits in a challenging continuous domain.

🧭 Keyword Pioneer — skill chaining
🐣 Hot Topic Early Bird — reinforcement learning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio
🌉 Interdisciplinary Bridge — Artificial Intelligence and Reinforcement Learning
📈 Trend Setter — Robotics

Authors

George Konidaris , Andrew G. Barto

Topics

Artificial Intelligence > Core AI > Agent Systems Reinforcement Learning > Methods > Deep RL Reinforcement Learning > Methods > Policy Learning Reinforcement Learning > Applications > Robotics Artificial Intelligence > Core AI > Robotics Artificial Intelligence > Core AI > Reinforcement Learning

Keywords

reinforcement learning hierarchical learning continuous control skill discovery skill chaining continuous domain
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