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Competitive Coevolution for micromanagement in StarCraft: Brood War
Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Context. Interest in and research on neural networks and their capacity for finding solutions to nonlinear problems has increased greatly in recent years.

Objectives. This thesis attempts to compare competitive coevolution to traditional neuroevolution in the game StarCraft: Brood War.

Methods. Implementing and evolving AI-controlled players for the game StarCraft and evaluating their performance.

Results. Fitness values and win rates against the default StarCraft AI and between the networks were gathered.

Conclusions. The neural networks failed to improve under the given circumstances. The best networks performed on par with the default StarCraft AI.

Place, publisher, year, edition, pages
2017.
Keyword [en]
neural networks, NEAT, StarCraft
National Category
Computer Science
Identifiers
URN: urn:nbn:se:bth-15377OAI: oai:DiVA.org:bth-15377DiVA: diva2:1152663
Subject / course
DV1478 Bachelor Thesis in Computer Science
Educational program
DVGSP Game Programming
Presentation
(English)
Available from: 2017-10-31 Created: 2017-10-25 Last updated: 2017-10-31Bibliographically approved

Open Access in DiVA

fulltext(713 kB)38 downloads
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Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf