Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89631
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dc.contributor.authorWang, Dien
dc.contributor.authorTan, Ah Hweeen
dc.date.accessioned2018-12-03T07:03:27Zen
dc.date.accessioned2019-12-06T17:29:54Z-
dc.date.available2018-12-03T07:03:27Zen
dc.date.available2019-12-06T17:29:54Z-
dc.date.copyright2015en
dc.date.issued2015en
dc.identifier.citationWang, D., & Tan, A. H. (2015). Creating autonomous adaptive agents in a real-time first-person shooter computer game. IEEE Transactions on Computational Intelligence and AI in Games, 7(2), 123-138. doi:10.1109/TCIAIG.2014.2336702en
dc.identifier.issn1943-068Xen
dc.identifier.urihttps://hdl.handle.net/10356/89631-
dc.description.abstractGames are good test-beds to evaluate AI methodologies. In recent years, there has been a vast amount of research dealing with real-time computer games other than the traditional board games or card games. This paper illustrates how we create agents by employing FALCON, a self-organizing neural network that performs reinforcement learning, to play a well-known first-person shooter computer game called Unreal Tournament. Rewards used for learning are either obtained from the game environment or estimated using the temporal difference learning scheme. In this way, the agents are able to acquire proper strategies and discover the effectiveness of different weapons without any guidance or intervention. The experimental results show that our agents learn effectively and appropriately from scratch while playing the game in real-time. Moreover, with the previously learned knowledge retained, our agent is able to adapt to a different opponent in a different map within a relatively short period of time.en
dc.description.sponsorshipNRF (Natl Research Foundation, S’pore)en
dc.format.extent16 p.en
dc.language.isoenen
dc.relation.ispartofseriesIEEE Transactions on Computational Intelligence and AI in Gamesen
dc.rights© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TCIAIG.2014.2336702].en
dc.subjectAdaptive Resonance Theory Operationsen
dc.subjectReal-time Computer Gameen
dc.subjectDRNTU::Engineering::Computer science and engineeringen
dc.titleCreating autonomous adaptive agents in a real-time first-person shooter computer gameen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen
dc.identifier.doi10.1109/TCIAIG.2014.2336702en
dc.description.versionAccepted versionen
dc.identifier.rims181369en
item.grantfulltextopen-
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