Deep learning and computer chess
This report presents a chess evaluation function trained using neural networks, without a priori knowledge of chess. The neural network undergoes two phases. In the first phase, it is trained using unsupervised learning to perform feature extraction. Subsequently in the second phase it undergoes...
Main Author: | Low, Benedict Yu |
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Other Authors: | He Ying |
Format: | Final Year Project (FYP) |
Language: | English |
Published: |
Nanyang Technological University
2021
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/153244 |
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