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AI Training Grounds: A study of adaptive AI in RPGs with lowstochastic dependence
University of Skövde, School of Informatics.
2019 (English)Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Artificial intelligence is used in video games for controlling AI agents but often follow astatic pre-defined behaviour. An AI capable of online learning would be able to adapttheir behaviour to whatever they may encounter. „Dynamic scripting‟ is one suchtechnique designed to be used in games with random outcomes. This study seeks toexamine if there is a measurable difference in the learning efficiency of dynamicscripting between games with stochastic outcomes and those with deterministicoutcomes. A CRPG was made with dynamic scripting implemented in charge of a teamof AI agents and a toggle to force deterministic or stochastic game rules. A series ofencounters against a static AI was then performed until the dynamic team was deemedeffective enough and the learning efficiency measured by how long this took. Theresults suggest a difference favouring dynamic scripting in deterministicenvironments.

Place, publisher, year, edition, pages
2019. , p. 18
Keywords [en]
video games, artificial intelligence, reinforcement learning, dynamic scripting
National Category
Computer Engineering Computer Sciences
Identifiers
URN: urn:nbn:se:his:diva-17077OAI: oai:DiVA.org:his-17077DiVA, id: diva2:1324522
Subject / course
Computer Science
Educational program
Computer Game Development - Design
Examiners
Available from: 2019-06-19 Created: 2019-06-13 Last updated: 2019-06-17Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
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  • de-DE
  • en-GB
  • en-US
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  • Other locale
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Output format
  • html
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  • asciidoc
  • rtf