Continual Online Evolutionary Planning for In-Game Build Order Adaptation in StarCraft

Niels Orsleff Justesen, Sebastian Risi

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

Abstract

The real-time strategy game StarCraft has become an important benchmark for AI research as it poses a complex environment with numerous challenges. An important strategic aspect in this game is to decide what buildings and units to produce. StarCraft bots playing in AI competitions today are only able to switch between predefined strategies, which makes it hard to adapt to new situations. This paper introduces an evolutionary-based method to overcome this challenge, called Continual Online Evolutionary Planning (COEP), which is able to perform in-game adaptive build-order planning. COEP was added to an open source StarCraft bot called UAlbertaBot and is able to outperform the built-in bots in the game as well as being competitive against a number of scripted opening strategies. The COEP augmented bot can change its build order dynamically and quickly adapt to the opponent’s strategy.
OriginalsprogEngelsk
TitelGECCO ’17 Proceedings of the Genetic and Evolutionary Computation Conference
ForlagAssociation for Computing Machinery
Publikationsdato16 jul. 2017
Sider187-194
ISBN (Trykt)978-1-4503-4920-8
DOI
StatusUdgivet - 16 jul. 2017
BegivenhedThe Genetic and Evolutionary Computation Conference - Berlin, Germany, Tyskland
Varighed: 15 jul. 201719 jul. 2017
http://gecco-2017.sigevo.org/index.html/HomePage

Konference

KonferenceThe Genetic and Evolutionary Computation Conference
LokationBerlin
Land/OmrådeTyskland
ByGermany
Periode15/07/201719/07/2017
Internetadresse

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