Evolving Complexity in Prediction Games.

07:00 EST 1st January 2019 | BioPortfolio

Summary of "Evolving Complexity in Prediction Games."

To study open-ended coevolution, we define a complexity metric over interacting finite state machines playing formal language prediction games, and study the dynamics of populations under competitive and cooperative interactions. In the past purely competitive and purely cooperative interactions have been studied extensively, but neither can successfully and continuously drive an arms race. We present quantitative results using this complexity metric and analyze the causes of varying rates of complexity growth across different types of interactions. We find that while both purely competitive and purely cooperative coevolution are able to drive complexity growth above the rate of genetic drift, mixed systems with both competitive and cooperative interactions achieve significantly higher evolved complexity.


Journal Details

This article was published in the following journal.

Name: Artificial life
ISSN: 1530-9185
Pages: 74-91


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Medical and Biotech [MESH] Definitions

Games designed to provide information on hypotheses, policies, procedure or strategies.

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Activity typically involving several individuals for the purpose of leisure, amusement, entertainment or pleasure.

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