Abstract
This paper explores the feasibility of computer simulation of evolving populations of social animals in nature, both from the anatomical and socio-environmental viewpoints, addressing the gap between the algorithms for evolution of digital objects, and the evolution of species in nature. The main components of ant body are mathematically described within the function representation framework; the parameters directly determine both the visual characteristics of the ant as well as the body characteristics encoded by the genome. The environmental diversification of ant subspecies is studied for fungus-growing ants, in which single-queen mating reproduction couples with large size of accessory male glands, while multiple-queen mating correlates to large size of accessory testes. Our results show that within an environment of restricted resources, both competing modes of sexual reproduction survive. The frequency with which either mode becomes dominant in the population is driven by the value of the mutation probability. The function representation model should be useful also in the simulation of other simple animal species, because of the ease in relating the genome parameters to computer visualization tools.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Baer, B., Boomsma, J.J.: Male reproductive investment and queen mating-frequency in fungus-frowing ants. Behavioral Ecology 15(3), 426–432 (2004)
Pasko, A., Adzhiev, V., Sourin, A., Savchenko, V.: Function representation in geometric modeling: concepts, implementation and applications. The Visual Computer 11(8), 429–446 (1995)
Pasko, A.A.: HyperFun Project, Hosei University, Japan (2006), http://cis.k.hosei.ac.jp/~F-rep/HF_proj.html
Masato, K.: An instance of HyperFun ant, http://cis.k.hosei.ac.jp/~F-rep/HF_ant.html
Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning, 3rd edn. Addison-Wesley, Reading (1989)
Shimizu, Y., Pichl, L.: HF-parameterized ant model, http://cpu.icu.ac.jp/~lukas/hfant/ant1.c
Marshall, J.A.R., Kovacs, T., Dornhaus, A.R., Franks, N.R.: Simulating the evolution of ant behaviour in evaluating nest sites. In: Banzhaf, W., Ziegler, J., Christaller, T., Dittrich, P., Kim, J.T. (eds.) ECAL 2003. LNCS (LNAI), vol. 2801, Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pichl, L., Shimizu, Y. (2006). Genetic Evolution of the Ant Species in Function Representation Framework. In: Wang, TD., et al. Simulated Evolution and Learning. SEAL 2006. Lecture Notes in Computer Science, vol 4247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11903697_83
Download citation
DOI: https://doi.org/10.1007/11903697_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-47331-2
Online ISBN: 978-3-540-47332-9
eBook Packages: Computer ScienceComputer Science (R0)