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About Lecture 1: Introduction To RL: Emma Brunskill
This document summarizes the key points from a lecture on reinforcement learning. The lecture included an overview of reinforcement learning, course logistics, and an introduction to sequential decision making under uncertainty. It discussed how reinforcement learning involves optimization, exploration, generalization, and dealing with delayed consequences. Examples of applications of reinforcement learning were provided, including Atari games, robotics, educational games, and healthcare. The differences between reinforcement learning and other machine learning paradigms such as AI planning, supervised learning, and imitation learning were also outlined.
Detailed Information
| Author: | ['Parth Gautam'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 78 |
| Language: | English |
| Format: | |
| Price: | FREE |
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