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Reinforcement Learning in Robotics

Reinforcement Learning in Robotics

[ˌriːɪnˈfɔːsmənt ˈlɜːrnɪŋ ɪn roʊˈbɒtɪks]
New Machine Learning
Last updated: 2026-06-05

Definition

Machine learning approach where robots learn optimal behaviors through trial and error.

Detailed Explanation

Reinforcement learning in robotics combines RL algorithms with physical systems. Addresses challenges of continuous state/action spaces, real-world sample complexity, and safety. May use simulation for training before real-world deployment.

Use Cases

Robot skill learning, Adaptive control, Game-playing robots, Autonomous exploration

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