Title :
Playing PuyoPuyo: Two search algorithms for constructing chain and tactical heuristics
Author :
Ikeda, Kokolo ; Tomizawa, Daisuke ; Viennot, Simon ; Tanaka, Yuu
Author_Institution :
Japan Adv. Inst. of Sci. & Technol., Ishikawa, Japan
Abstract :
Tetris is one of the most famous tile-matching video games, and has been used as a test bed for artificial intelligence techniques such as machine learning. Many games have been derived from such early tile-matching games, in this paper we discuss how to develop AI players of "PuyoPuyo". PuyoPuyo is a popular two-player game, and where the main point is to construct a "chain" longer than the opponent. We introduce two tree search algorithms and some tactical heuristics for improving the performance. We were able to reach an average chain length of 11, notably higher than that of the commercial Als.
Keywords :
computer games; learning (artificial intelligence); search problems; trees (mathematics); AI players; PuyoPuyo; Tetris; artificial intelligence techniques; chain length; machine learning; performance improvement; tactical heuristics; test bed; tile-matching video games; tree search algorithms; two-player game; Computational intelligence; Conferences; Games;
Conference_Titel :
Computational Intelligence and Games (CIG), 2012 IEEE Conference on
Conference_Location :
Granada
Print_ISBN :
978-1-4673-1193-9
Electronic_ISBN :
978-1-4673-1192-2
DOI :
10.1109/CIG.2012.6374140
