New Heuristics for Monte Carlo Tree Search Applied to the Game of Go
博士 === 國立臺灣師範大學 === 資訊工程研究所 === 99 === Research into computer Go started around 1970, but the Go-playing programs were never, in a real sense, considered to be strong until the year 2006, when the brand new search scheme Monte Carlo Tree Search (MCTS) and Upper Confidence bounds applied to Trees (UC...
Main Authors: | Shih-Chieh Huang, 黃士傑 |
---|---|
Other Authors: | Shun-Shii Lin |
Format: | Others |
Language: | en_US |
Published: |
2011
|
Online Access: | http://ndltd.ncl.edu.tw/handle/33778013275021463828 |
Similar Items
-
Apply Deep Learning and Monte Carlo Tree Search on Block Go
by: Jhao-Shen Chen, et al.
Published: (2017) -
Applying Monte Carlo Tree Search to Tien Gow Game
by: CHUNG,KUAN-LIN, et al.
Published: (2016) -
Parallel Go on CUDA with Monte Carlo Tree Search
by: Zhou, Jun
Published: (2013) -
Go Go! - Evaluating Different Variants of Monte Carlo Tree Search for Playing Go
by: Frendin, Carl, et al.
Published: (2014) -
Improving Monte Carlo Tree Search with Artificial Neural Networks without Heuristics
by: Alba Cotarelo, et al.
Published: (2021-02-01)