TAAFT
Free mode
100% free
Freemium
Free Trial
Deals
Create tool
Glossary
Machine Learning
Reinforcement Learning in Robotics

Reinforcement Learning in Robotics

[ˌriːɪnˈfɔːsmənt ˈlɜːrnɪŋ ɪn roʊˈbɒtɪks]
Machine Learning
Last updated: December 9, 2024

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

Related Terms

Stacking

Combining multiple models using a meta-model for predictions.

Machine Learning

Latent Dirichlet Allocation

A generative statistical model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar.

Machine Learning

Andrew Ng

AI educator and entrepreneur who co-founded Coursera and deeplearning.ai, making AI education accessible to millions worldwide.

Machine Learning