Lecture

Reinforcement Learning: Q-Learning

Description

This lecture introduces the concept of reinforcement learning, focusing on Q-Learning as a model-free method for agents to learn by trial-and-error. It covers the exploration-exploitation trade-off, action values, and policies. The lecture also discusses the convergence properties of Q-Learning, the importance of human-compatible AI, and the impact of algorithms on society.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_38vn8zck

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Ontological neighbourhood

Information engineering

Machine learning: Reinforcement learning

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