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Reactiveness and navigation in computer games : different needs, different approaches
Date Issued
2011-08-31
Date Available
2012-02-21T17:26:09Z
Abstract
This paper presents an approach to the Mario AI Benchmark problem, using the A* algorithm for navigation, and an evolutionary process combining routines for the reactiveness of the resulting bot. The Grammatical Evolution system was used to evolve Behaviour Trees, combining both types of routines, while the highly dynamic nature of the environment required specific approaches to deal with over-fitting issues. The results obtained highlight the need for specific algorithms for the different aspects of controlling a bot in a game environment, while Behaviour Trees provided the perfect representation to combine all those algorithms.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2011 IEEE
Keywords
Subject – LCSH
Evolutionary computation
Genetic programming (Computer science)
Computer games--Programming
Web versions
Language
English
Status of Item
Peer reviewed
Part of
2011 IEEE Conference on Computational Intelligence and Games (CIG) [proceedings]
Conference Details
Paper presented at the 2011 IEEE Conference on Computational Intelligence and Games (CIG’11), Seoul, South Korea, August 31st-September 3rd 2011
ISBN
978-1-4577-0010-1
This item is made available under a Creative Commons License
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