Rapid adaptation of video game AI

Sander Bakkes*, Pieter Spronck, Jaap van den Herik

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Current approaches to adaptive game AI require either a high quality of utilised domain knowledge, or a large number of adaptation trials. These requirements hamper the goal of rapidly adapting game AI to changing circumstances. In an alternative, novel approach, domain knowledge is gathered automatically by the game AI, and is immediately (i.e., without trials and without resource-intensive learning) utilised to evoke effective behaviour. In this paper we discuss this approach, called 'rapidly adaptive game AI'. We perform experiments that apply the approach in an actual video game. From our results we may conclude that rapidly adaptive game AIprovides a strong basis for effectively adapting game AI in actual video games.

Original languageEnglish
Title of host publication9th International Conference on Intelligent Games and Simulation, GAME-ON 2008
Pages69-76
Number of pages8
Publication statusPublished - 2008
Event9th International Conference on Intelligent Games and Simulation, GAME-ON 2008 - Valencia, Spain
Duration: 17 Nov 200819 Nov 2008

Publication series

Name9th International Conference on Intelligent Games and Simulation, GAME-ON 2008

Conference

Conference9th International Conference on Intelligent Games and Simulation, GAME-ON 2008
Country/TerritorySpain
CityValencia
Period17/11/0819/11/08

Bibliographical note

Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.

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