Imitating reactive human behaviours in games using neural networks
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/158176
comunitat-uji-handle2:10234/71324
comunitat-uji-handle3:10234/169451
comunitat-uji-handle4:
TFG-TFMMetadatos
Título
Imitating reactive human behaviours in games using neural networksAutoría
Tutor/Supervisor; Universidad.Departamento
García Fernández, Luis Amable; Universitat Jaume I. Departament d'Enginyeria i Ciència dels ComputadorsFecha de publicación
2020-07-09Editor
Universitat Jaume IResumen
Deep learning has allowed to create neural networks that can play any game almost
optimally. However, not so many have been trained to play like humans, or more concretely,
like one specific person. Most people have ... [+]
Deep learning has allowed to create neural networks that can play any game almost
optimally. However, not so many have been trained to play like humans, or more concretely,
like one specific person. Most people have recognizable ways of playing specific
games, and imitating those behaviors would allow to create bots that don’t appear to
be artificially generated. Also, by imitating one person behaviors it would be easy to
create bots that play at the same level of quality.
This document, which is a Final Degree Work report for the Bachelor’s Degree in
Video Game Design and Development, presents some techniques to create neural networks
that can imitate human behaviors using Unity’s ML Agents SDK, an analysis
on what behaviors can be modeled more precisely, what are the training costs and how
good are the results. [-]
Palabras clave / Materias
Descripción
Treball final de Grau en Disseny i Desenvolupament de Videojocs. Codi: VJ1241. Curs acadèmic: 2019/2020
Tipo de documento
info:eu-repo/semantics/bachelorThesisDerechos de acceso
info:eu-repo/semantics/openAccess
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