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About Alpha Go Zero Pseudo Code
This document provides an overview of AlphaGo Zero, including: 1) A brief pseudo code for AlphaGo Zero's training algorithm, which uses a policy iteration procedure incorporating Monte Carlo tree search and self-play reinforcement learning. 2) Key differences between AlphaGo Zero and previous AlphaGo versions, such as learning from random self-play without human data. 3) Main components of AlphaGo Zero's self-play training pipeline including continually optimizing the neural network and evaluating players.
Detailed Information
| Author: | ['TheDreamM'] |
|---|---|
| Publication Year: | 2017 |
| Pages: | 3 |
| Language: | English |
| Format: | |
| Price: | FREE |
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