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About 1 Introduction To RL
This document provides an overview of a deep reinforcement learning course at UC Berkeley. It discusses course logistics, prerequisites, what will be covered in the course, assignments, and an introduction to reinforcement learning and why it is important. The key topics covered are: deep reinforcement learning, examples of reinforcement learning problems, why we should study this now given advances in deep learning and computational power, and other challenges that need to be addressed to enable real-world sequential decision making applications.
Detailed Information
| Author: | ['Nathaniel Saura'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 46 |
| Language: | English |
| Format: | |
| Price: | FREE |
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