Evolving behaviour trees for the commercial game DEFCON

Chong U. Lim, Robin Baumgarten, Simon Colton

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

91 Citations (Scopus)


Behaviour trees provide the possibility of improving on existing Artificial Intelligence techniques in games by being simple to implement, scalable, able to handle the complexity of games, and modular to improve reusability. This ultimately improves the development process for designing automated game players. We cover here the use of behaviour trees to design and develop an AI-controlled player for the commercial real-time strategy game DEFCON. In particular, we evolved behaviour trees to develop a competitive player which was able to outperform the game's original AI-bot more than 50% of the time. We aim to highlight the potential for evolving behaviour trees as a practical approach to developing AI-bots in games.

Original languageEnglish
Title of host publicationApplications of Evolutionary Computation - EvoApplicatons 2010
Subtitle of host publicationEvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, Proceedings
Number of pages11
EditionPART 1
Publication statusPublished - 21 May 2010
Externally publishedYes
EventEuropean Workshop on Bio-inspired Algorithms in Games 2010 - Istanbul, Türkiye
Duration: 7 Apr 20109 Apr 2010
Conference number: 2nd
https://link.springer.com/book/10.1007/978-3-642-12239-2 (Proceedings)

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6024 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


WorkshopEuropean Workshop on Bio-inspired Algorithms in Games 2010
Abbreviated titleEvoGAMES 2010
Internet address

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