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2017 | OriginalPaper | Buchkapitel

Resource Production in StarCraft Based on Local Search and Planning

verfasst von : Thiago F. Naves, Carlos R. Lopes

Erschienen in: Computational Science and Its Applications – ICCSA 2017

Verlag: Springer International Publishing

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Abstract

This paper describes a approach for resource production in real-time strategy games (RTS Games). RTS games is a research area that presents interesting challenges for planning of concurrent actions, satisfaction of preconditions and resource management. Rather than working with fixed goals for resource production, we aim at achieving goals that maximize real-time resource production. The approach uses the Simulated Annealing (SA) algorithm as a search tool for deriving resource production goals. The authors have also developed a planning system that works in conjunction with SA to operate properly in a real-time environment. Analysis of performance compared to human and bot players corroborate in confirming the efficiency of our approach and the claims we have made.

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Vorheriges Kapitel Adaptive Sine Cosine Algorithm Integrated with Differential Evolution for Structural Damage Detection

Nächstes Kapitel Inductive Synthesis of the Models of Biological Systems According to Clinical Trials

StarCraft Competition is a competition between Starcraft bots, this competition is an event that is part of AIIDE (AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment).

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Titel: Resource Production in StarCraft Based on Local Search and Planning
verfasst von: Thiago F. Naves
Carlos R. Lopes
Verlag: Springer International Publishing
Buch: Computational Science and Its Applications – ICCSA 2017
Print ISBN: 978-3-319-62391-7

Electronic ISBN: 978-3-319-62392-4

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-62392-4_7

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