5 papers · 1 filter
A Study of Solving Life-and-Death Problems in Go Using Relevance-Zone Based Solvers
Chung-Chin Shih, Ti-Rong Wu, Ting Han Wei +3
This paper analyzes the behavior of solving Life-and-Death (L&D) problems in the game of Go using current state-of-the-art computer Go solvers with two techniques: the Relevance-Zo…
Relevance-Zone Reduction in Game Solving
Chi-Huang Lin, Ting Han Wei, Chun-Jui Wang +5
Game solving aims to find the optimal strategies for all players and determine the theoretical outcome of a game. However, due to the exponential growth of game trees, many games r…
Solving 7x7 Killall-Go with Seki Database
Yun-Jui Tsai, Ting Han Wei, Chi-Huang Lin +4
Game solving is the process of finding the theoretical outcome for a game, assuming that all player choices are optimal. This paper focuses on a technique that can reduce the heuri…
Game Solving with Online Fine-Tuning
Ti-Rong Wu, Hung Guei, Ting Han Wei +3
Game solving is a similar, yet more difficult task than mastering a game. Solving a game typically means to find the game-theoretic value (outcome given optimal play), and optional…
MiniZero: Comparative Analysis of AlphaZero and MuZero on Go, Othello, and Atari Games
Ti-Rong Wu, Hung Guei, Pei-Chiun Peng +4
This paper presents MiniZero, a zero-knowledge learning framework that supports four state-of-the-art algorithms, including AlphaZero, MuZero, Gumbel AlphaZero, and Gumbel MuZero.…