6 papers
Evaluating Game Difficulty in Tetris Block Puzzle
Chun-Jui Wang, Jian-Ting Guo, Hung Guei +3
Tetris Block Puzzle is a single player stochastic puzzle in which a player places blocks on an 8 x 8 grid to complete lines; its popular variants have amassed tens of millions of d…
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…
OptionZero: Planning with Learned Options
Po-Wei Huang, Pei-Chiun Peng, Hung Guei +1
Planning with options -- a sequence of primitive actions -- has been shown effective in reinforcement learning within complex environments. Previous studies have focused on plannin…
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…
Demystifying MuZero Planning: Interpreting the Learned Model
Hung Guei, Yan-Ru Ju, Wei-Yu Chen +1
MuZero has achieved superhuman performance in various games by using a dynamics network to predict the environment dynamics for planning, without relying on simulators. However, th…