Improving behavior of computer game bots using fictitious play.

摘要

In modern computer games, 'bots'---Intelligent realistic agents play a prominent role in success of a game in the market. Typically, bots are modeled using finite-state machine and then programmed via simple conditional statements which are hard-coded in bots logic. Since these bots have become quite predictable to an experienced games' player, a player might lose interest in the game. We propose the use of a game theoretic based learning rule called Fictitious Play for improving behavior of these computer game bots which will make them less predictable and hence, more enjoyable to a game player.