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Hybrid pathfinding in StarCraft
Linnaeus University, Faculty of Technology, Department of Computer Science.ORCID iD: 0000-0002-8591-1035
2016 (English)In: IEEE Transactions on Computational Intelligence and AI in Games, ISSN 1943-068X, E-ISSN 1943-0698, Vol. 8, no 4, 319-324 p., 7063238Article in journal (Refereed) Published
Abstract [en]

Micro-management is a very important aspect of RTS games. It involves moving single units or groups of units effectively on the battle field, targeting the most threatening enemy units and use the unit's special abilities when they are the most harmful for the enemy or the most beneficial for the player. Designing good micro-management is a challenging task for AI bot developers. In this paper we address the micro-management sub-task of positioning units effectively in combat situations. Two different approaches are evaluated, one based on potential fields and the other based on flocking algorithms. The results show that both the potential fields version and the flocking version clearly increases the win percentage of the bot, but the difference in wins between the two is minimal. The results also show that the more flexible potential fields technique requires much more hardware resources than the more simple flocking technique.

Place, publisher, year, edition, pages
2016. Vol. 8, no 4, 319-324 p., 7063238
National Category
Computer Science
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-58295DOI: 10.1109/TCIAIG.2015.2414447ISI: 000391470800002Scopus ID: 2-s2.0-84990938462OAI: oai:DiVA.org:lnu-58295DiVA: diva2:1049642
Available from: 2016-11-25 Created: 2016-11-25 Last updated: 2017-02-10Bibliographically approved

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