Analyzing the impact of knowledge and search in Monte Carlo Tree Search in Go

• Author / Creator

  Farhad Haqiqat

• Domain-specific knowledge plays a significant role in the success of many Monte Carlo Tree Search (MCTS) programs. The details of how knowledge affects MCTS are still not well understood. In this thesis, we focus on identifying the effects of different types of knowledge on the behaviour of the Monte Carlo Tree Search algorithm, using the game of Go as a case study. We measure the performance of each type of knowledge, and of deeper search by using two main metrics: The move prediction rate on games played by professional players, and the playing strength of an implementation in our program Fuego.
  We compare the result of these two evaluation methods in detail, in order
  to understand how effective they are in fully understanding a program’s be-
  haviour. A feature-based approach refines our analysis tools, and addresses
  some of the shortcomings of these two evaluation methods. This approach
  allows us to interpret different components of knowledge and deeper search in
  different phases of a game, and helps us to obtain a deeper understanding of
  the role of knowledge and its relation with search in the MCTS algorithm.

• Subjects / Keywords

  • Monte Carlo Tree Search
  • Go
  • Search
  • Knowledge
  • Evaluation

• Graduation date

  Fall 2018

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R30000G42

• License

  Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.