Co-evolutionary particle swarm optimization applied to the 7×7 Seega game
Ashraf M. Abdelbar, Sherif Ragab, Sara Mitri · 2005
Seega is an ancient Egyptian two-stage board game that, in certain aspects, is more difficult than chess. The two-player game is most commonly played on a 7 /spl times/ 7 board, but is also sometimes played on a 5 /spl times/ 5 or 9 /spl times/ 9 board. In the first and more difficult stage of the game, players take turns placing one disk each on the board until the board contains only one empty cell. In the second stage players take turns moving disks of their color; a disk that becomes surrounded by disks of the opposite color is captured and removed from the board. Building on previous work, on the 5 /spl times/ 5 version of Seega [A.M. Abdelbar et al., 2003], we focus, in this paper, on the 7 /spl times/ 7 board. Our approach employs co-evolutionary particle swarm optimization for the generation of feature evaluation scores. Two separate swarms are used to evolve White players and Black players, respectively; each particle represents feature weights for use in the position evaluation. Experimental results are presented and the performance of the full game engine are discussed.