Evolutionary Neural Network for Othello Game

被引:2
作者
Gunawan [1 ]
Armanto, Hendrawan [1 ]
Santoso, Joan [1 ]
Giovanni, Daniel [1 ]
Kurniawan, Faris [1 ]
Yudianto, Ricky [1 ]
Steven [1 ]
机构
[1] Sekolah Tinggi Tekn Surabaya, Dept Comp Sci, Ngagel Jaya Tengah 73-77, Surabaya 60284, Indonesia
来源
INTERNATIONAL CONFERENCE ON ASIA PACIFIC BUSINESS INNOVATION AND TECHNOLOGY MANAGEMENT | 2012年 / 57卷
关键词
Game Playing; Neural Network; Reversi; Genetic; Evolutionary Neural Network;
D O I
10.1016/j.sbspro.2012.09.1206
中图分类号
F [经济];
学科分类号
02 ;
摘要
Game playing is a game method that require an AI (Artificial Intelligence), so that an AI can play against human in a game. Artificial intelligence involves two basic ideas[4]. First, it involves studying the thought processes of human beings. Second, it deals with representing those processes via machines (like computers, robots, etc.). AI is behavior of a machine, which, if performed by a human being, would be called intelligent. It makes machines smarter and more useful, and is less expensive than natural intelligence. Othello is one example of game playing using AI. Even though it may appear as though Othello is a fairly simple game, there still are many important aspects of the game to consider. The most important of these are the evaluation function and searching algorithms. Why are these important? First of all, the game would be nothing without an evaluation function. And there are many interesting aspects of the evaluation which can greatly affect both efficiency as well as game play. Second, a good searching algorithm can fulfill the ideal properties of a good heuristic, providing a good answer in a reasonable amount of time. (C) 2012 Published by Elsevier Ltd.
引用
收藏
页码:419 / 425
页数:7
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