Channon, AD ORCID: https://orcid.org/0000-0001-9224-4931 (2019) Maximum Individual Complexity is Indefinitely Scalable in Geb. Artificial Life. (In Press)

WarningThere is a more recent version of this item available.
[img]
Preview
Text
channon-ArtificialLifeJournal2019a-authorsFinalVersion.pdf - Accepted Version

Download (551kB) | Preview

Abstract

Geb was the first artificial life system to be classified as exhibiting open-ended evolutionary dynamics according to Bedau and Packard’s evolutionary activity measures and is the only one to have been classified as such according to the enhanced version of that classification scheme. Its evolution is driven by biotic selection, that is (approximately) by natural selection rather than artificial selection. Whether or not Geb can generate an indefinite increase in maximum individual complexity is evaluated here by scaling two parameters: world length (which bounds population size) and the maximum number of neurons per individual. Maximum individual complexity is found to be asymptotically bounded when scaling either parameter alone. However, maximum individual complexity is found to be indefinitely scalable, to the extent evaluated so far (with runtimes in years and billions of reproductions per run), when scaling both world length and the maximum number of neurons per individual, together. Further, maximum individual complexity is shown to scale logarithmically with (the lower of) maximum population size and maximum number of neurons per individual. This raises interesting questions and lines of thought about the feasibility of achieving complex results within open-ended evolutionary systems and how to improve on this order of complexity growth.

Item Type: Article
Additional Information: © MIT Press. This is the accepted author manuscript (AAM). The final published version (version of record) will be available online via MIT Press at https://www.mitpressjournals.org/loi/artl - please refer to any applicable terms of use of the publisher.
Uncontrolled Keywords: open-ended evolution, biotic selection, ongoing growth of complexity, diversity, indefinite scalability
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Natural Sciences > School of Computing and Maths
Depositing User: Symplectic
Date Deposited: 20 Feb 2019 14:01
Last Modified: 26 Feb 2019 13:50
URI: http://eprints.keele.ac.uk/id/eprint/5900

Available Versions of this Item

Actions (login required)

View Item View Item