Lecture

Reinforcement Learning Basics

Description

This lecture covers the fundamentals of reinforcement learning, focusing on topics such as Q-learning, epsilon-greedy policies, and Monte Carlo estimation. It explains how agents interact with environments, learn optimal policies, and balance exploration and exploitation.

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Official source

https://mediaspace.epfl.ch/media/0_h4q5epi2

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Ontological neighbourhood

Information engineering

Machine learning: Reinforcement learning

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