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Creating Human-like AI Movement in Games Using Imitation Learning
KTH, School of Computer Science and Communication (CSC).
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Imitation Learning som verktyg för att skapa människolik rörelse för AI-karaktärer i spel (Swedish)
Abstract [en]

The way characters move and behave in computer and video games are important factors in their believability, which has an impact on the player’s experience. This project explores Imitation Learning using limited amounts of data as an approach to creating human-like AI behaviour in games, and through a user study investigates what factors determine if a character is human-like, when observed through the characters first-person perspective. The idea is to create or shape AI behaviour by recording one's own actions. The implemented framework uses a Nearest Neighbour algorithm with a KD-tree as the policy which maps a state to an action. Results showed that the chosen approach was able to create human-like AI behaviour while respecting the performance constraints of a modern 3D game.

Abstract [sv]

Sättet karaktärer rör sig och beter sig på i dator- och tvspel är viktiga faktoreri deras trovärdighet, som i sin tur har en inverkan på spelarens upplevelse. Det här projektet utforskar Imitation Learning med begränsad mängd data som etttillvägagångssätt för att skapa människolik rörelse för AI-karaktärer i spel, ochutforskar genom en användarstudie vilka faktorer som avgör om en karaktärär människolik, när karaktären observeras genom dess förstapersonsperspektiv. Iden är att skapa eller forma AI-beteende genom att spela in sina egna handlingar. Det implementerade ramverket använder en Nearest Neighbour-algoritmmed ett KD-tree som den policy som kopplar ett tillstånd till en handling. Resultatenvisade att det valda tillvägagångssättet lyckades skapa människolikt AI-beteende samtidigt som det respekterar beräkningskomplexitetsrestriktionersom ett modernt 3D-spel har.

Place, publisher, year, edition, pages
2017. , p. 51
Keyword [en]
imitation learning, games, ai, artificial intelligence, human, human-like, unpredictable ai, copy synthesis, performance, unity
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-210887OAI: oai:DiVA.org:kth-210887DiVA, id: diva2:1120710
External cooperation
Fast Travel Games AB
Subject / course
Computer Technology, Program- and System Development
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2017-10-16 Created: 2017-07-06 Last updated: 2018-01-13Bibliographically approved

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Casper Renman Master's Thesis(4724 kB)51 downloads
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