Online Adaptive Controller for Simulated Car Racing

C. H. Tan; J. H. Ang; K. C. Tan; A. Tay

doi:10.1109/CEC.2008.4631096

Online Adaptive Controller for Simulated Car Racing

C. H. Tan
, J. H. Ang
, K. C. Tan
, A. Tay

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

13 Citations (Scopus)

Abstract

An adaptive game AI has the potential of tailoring a uniquely entertaining and meaningful game experience to a specific player. An online adaptive AI should be able to profile its opponent efficiently during the early phase of the game and adapts its own playing style to the level of the player so that the player feels entertained playing against it. This paper presents an online adaptive algorithm that uses ideas from evolutionary computation to match the skill level of the opponent during the game. The proposed algorithms demonstrated using a car racing simulator is capable of matching its opponents in terms of both mean score and winning percentages.

Original language	English
Title of host publication	2008 IEEE Congress on Evolutionary Computation (CEC 2008)
Pages	2239-2245
DOIs	https://doi.org/10.1109/CEC.2008.4631096
Publication status	Published - Jun 2008
Externally published	Yes
Event	2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong Convention and Exhibition Centre, Hong Kong, China Duration: 1 Jun 2008 → 6 Jun 2008

Conference

Conference	2008 IEEE Congress on Evolutionary Computation, CEC 2008
Place	China
City	Hong Kong
Period	1/06/08 → 6/06/08

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title = "Online Adaptive Controller for Simulated Car Racing",

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year = "2008",

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AB - An adaptive game AI has the potential of tailoring a uniquely entertaining and meaningful game experience to a specific player. An online adaptive AI should be able to profile its opponent efficiently during the early phase of the game and adapts its own playing style to the level of the player so that the player feels entertained playing against it. This paper presents an online adaptive algorithm that uses ideas from evolutionary computation to match the skill level of the opponent during the game. The proposed algorithms demonstrated using a car racing simulator is capable of matching its opponents in terms of both mean score and winning percentages.

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M3 - RGC 32 - Refereed conference paper (with host publication)

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EP - 2245

BT - 2008 IEEE Congress on Evolutionary Computation (CEC 2008)

T2 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008

Y2 - 1 June 2008 through 6 June 2008

ER -

Online Adaptive Controller for Simulated Car Racing

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