Learning environment models in car racing using stateful genetic programming

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Title: Learning environment models in car racing using stateful genetic programming
Authors: Agapitos, Alexandros
O'Neill, Michael
Brabazon, Anthony
Theodoridis, Theodoros
Permanent link: http://hdl.handle.net/10197/3573
Date: 31-Aug-2011
Online since: 2012-04-17T13:57:05Z
Abstract: For computational intelligence to be useful in creating game agent AI we need to focus on methods that allow the creation and maintenance of models for the environment, which the artificial agents inhabit. Maintaining a model allows an agent to plan its actions more effectively by combining immediate sensory information along with a memories that have been acquired while operating in that environment. To this end, we propose a way to build environment models for non-player characters in car racing games using stateful Genetic Programming. A method is presented, where general purpose 2-dimensional data-structures are used to build a model of the racing track. Results demonstrate that model-building behaviour can be cooperatively coevolved with car controlling behaviour in modular programs that make use of these models in order to navigate successfully around a racing track.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: IEEE
Copyright (published version): © 2011 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.
Keywords: Video gameGenetic programming
Subject LCSH: Video games
Genetic programming (Computer science)
Machine learning
DOI: 10.1109/CIG.2011.6032010
Other versions: http://dx.doi.org/10.1109/CIG.2011.6032010
Language: en
Status of Item: Peer reviewed
Is part of: 2011 IEEE Conference on Computational Intelligence and Games [proceedings]
Conference Details: Paper presented at the 2011 IEEE Conference on Computational Intelligence and Games (CIG’11), Seoul, South Korea, Aug.31-Sept.3, 2011
ISBN: 978-1-4577-0009-5
Appears in Collections:Computer Science Research Collection
Business Research Collection
CASL Research Collection

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