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

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Standard

Continual Online Evolutionary Planning for In-Game Build Order Adaptation in StarCraft. / Justesen, Niels Orsleff; Risi, Sebastian.

GECCO ’17 Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery, 2017. p. 187-194.

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Harvard

Justesen, NO & Risi, S 2017, Continual Online Evolutionary Planning for In-Game Build Order Adaptation in StarCraft. in GECCO ’17 Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery, pp. 187-194, The Genetic and Evolutionary Computation Conference, Germany, Germany, 15/07/2017. https://doi.org/10.1145/3071178.3071210

APA

Justesen, N. O., & Risi, S. (2017). Continual Online Evolutionary Planning for In-Game Build Order Adaptation in StarCraft. In GECCO ’17 Proceedings of the Genetic and Evolutionary Computation Conference (pp. 187-194). Association for Computing Machinery. https://doi.org/10.1145/3071178.3071210

Vancouver

Justesen NO, Risi S. Continual Online Evolutionary Planning for In-Game Build Order Adaptation in StarCraft. In GECCO ’17 Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery. 2017. p. 187-194 https://doi.org/10.1145/3071178.3071210

Author

Justesen, Niels Orsleff ; Risi, Sebastian. / Continual Online Evolutionary Planning for In-Game Build Order Adaptation in StarCraft. GECCO ’17 Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery, 2017. pp. 187-194

Bibtex

@inproceedings{0ea9a6bed10646bd8d1cde77b358f870,
title = "Continual Online Evolutionary Planning for In-Game Build Order Adaptation in StarCraft",
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.",
author = "Justesen, {Niels Orsleff} and Sebastian Risi",
year = "2017",
month = "7",
day = "16",
doi = "10.1145/3071178.3071210",
language = "English",
isbn = "978-1-4503-4920-8",
pages = "187--194",
booktitle = "GECCO ’17 Proceedings of the Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery",
address = "United States",

}

RIS

TY - GEN

T1 - Continual Online Evolutionary Planning for In-Game Build Order Adaptation in StarCraft

AU - Justesen, Niels Orsleff

AU - Risi, Sebastian

PY - 2017/7/16

Y1 - 2017/7/16

N2 - 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.

AB - 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.

U2 - 10.1145/3071178.3071210

DO - 10.1145/3071178.3071210

M3 - Article in proceedings

SN - 978-1-4503-4920-8

SP - 187

EP - 194

BT - GECCO ’17 Proceedings of the Genetic and Evolutionary Computation Conference

PB - Association for Computing Machinery

ER -

ID: 81965008