Discovering Agent Behaviours through Code Reuse: Examples from Half-Field Offense and Ms. Pac-Man
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @Article{Kelly:2017:ieeeTCIAIgames,
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author = "Stephen Kelly and Malcolm I. Heywood",
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title = "Discovering Agent Behaviours through Code Reuse:
Examples from Half-Field Offense and {Ms. Pac-Man}",
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journal = "IEEE Transactions on Games",
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year = "2018",
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volume = "10",
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number = "2",
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pages = "195--208",
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month = jun,
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keywords = "genetic algorithms, genetic programming, code reuse,
coevolution, half-field offense (HFO), Ms Pac-Man, task
transfer",
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DOI = "doi:10.1109/TCIAIG.2017.2766980",
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ISSN = "1943-068X",
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size = "14 pages",
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abstract = "This work demonstrates how code reuse allows genetic
programming (GP) to discover strategies for difficult
gaming scenarios while maintaining relatively low model
complexity. Critical factors in the proposed approach
are illustrated through an in-depth study in two
challenging task domains: RoboCup Soccer and Ms.
Pac-Man. In RoboCup, we demonstrate how policies
initially evolved for simple subtasks can be reused,
with no additional training or transfer function, in
order to improve learning in the complex Half Field
Offense (HFO) task. We then show how the same approach
to code reuse can be applied directly in Ms. Pac-Man.
In the later case, the use of task-agnostic diversity
maintenance removes the need to explicitly identify
suitable subtasks a priori. The resulting GP policies
achieve state-of-the-art levels of play in HFO and
surpass scores previously reported in the Ms. Pac-Man
literature, while employing less domain knowledge
during training. Moreover, the highly modular policies
discovered by GP are shown to be significantly less
complex than state-of-the-art solutions in both
domains. Throughout this work we pay special attention
to a pair of task-agnostic diversity maintenance
techniques, and empirically demonstrate their
importance to the development of strong policies.",
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notes = "Also known as \cite{8085186}",
- }
Genetic Programming entries for
Stephen Kelly
Malcolm Heywood
Citations