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Artificial endosymbiosis

Bull, Lawrence; Pipe, A. G.; Bull, Larry; Pipe, Anthony G.; Fogarty, Terence C.

Authors

Lawrence Bull

A. G. Pipe

Lawrence Bull Larry.Bull@uwe.ac.uk
AHOD Research and Scholarship and Prof

Terence C. Fogarty



Contributors

Almeida e Costa Fernando
Editor

Abstract

© Springer-Verlag Berlin Heidelberg 1995. Symbiosis is the phenomenon in which organisms of different species live together in close association, resulting in a raised level of fitness for one or more of the organisms. Endosymbiosis is the name given to symbiotic relationships in which partners are contained within a host partner. In this paper we use a simulated model of coevolution to examine endosymbiosis and its effect on the evolutionary performance of the partners involved. We are then able to suggest the conditions under which endosymbioses are more likely to occur and why; we find they emerge between organisms within a window of their respective "chaotic gas regimes" and hence that the association represents a more stable state for the partners. An endosymbiosis’ effect on its other ecological partners’ evolution is also examined. The results are used as grounds for allowing endosymbioses to emerge within artificial coevolutionary multi-agent systems.

Journal Article Type Conference Paper
Publication Date Jan 1, 1995
Journal Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Print ISSN 0302-9743
Electronic ISSN 1611-3349
Publisher Springer Verlag
Peer Reviewed Not Peer Reviewed
Volume 929
Pages 273-289
Series Title Lecture Notes in Computer Science
Series Number 4648
ISBN ;
APA6 Citation Pipe, A. G., Bull, L., Bull, L., Fogarty, T. C., & Pipe, A. G. (1995). Artificial endosymbiosis. Lecture Notes in Artificial Intelligence, 929, 273-289. https://doi.org/10.1007/3-540-59496-5_305
DOI https://doi.org/10.1007/3-540-59496-5_305
Keywords artificial intelligence, computer applications in Life Sciences,
mathematical biology in general, statistics for life sciences, medicine, health sciences, neurosciences, combinatorics
Publisher URL http://dx.doi.org/10.1007/3-540-59496-5_305