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Comparing the performance of the evolvable πgrammatical evolution genotype-phenotype pap to grammatical evolution in the dynamic Ms. Pac-Man environment
Date Issued
2010-07
Date Available
2010-11-22T15:06:31Z
Abstract
In this work, we examine the capabilities of two forms of mappings by means of Grammatical Evolution (GE) to successfully generate controllers by combining high-level functions in a dynamic environment. In this work we adopted the Ms. Pac-Man game as a benchmark test bed. We show that the standard GE mapping and Position Independent GE (πGE) mapping achieve similar performance in terms of maximising the score. We also show that the controllers produced by both approaches have an overall better performance in terms of maximising the score compared to a hand-coded agent. There are, however, significant differences in the controllers produced by these two approaches: standard GE produces more controllers with invalid code, whereas the opposite is seen with πGE.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2010 IEEE
Subject – LCSH
Genetic programming (Computer science)
Genetic algorithms
Computer games
Ms. Pac-Man Maze Madness (Game)
Web versions
Language
English
Status of Item
Peer reviewed
Part of
Evolutionary Computation (CEC), 2010 IEEE Congress on [proceedings]
Conference Details
IEEE World Congress on Computational Intelligence, Barcelona, Spain, 18-23 July
ISBN
978-1-4244-6909-3
This item is made available under a Creative Commons License
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