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Application and development of biologically plausible neural networks in a multiagent artificial life system

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Abstract

The present article introduces the system BioAnt, which is a computational simulation of a small colony of ants (up to 99 members) in which every ant relies on a biologically more plausible artificial neural networks as control mechanism for guidance. The environment, in which the ants are placed, is three-dimensional, consisting of the anthill, sugar, water, earth elevations, walls and predators. The ants’ foraging behavior was successfully implemented as well as some basic defense mechanisms. Typical sensors and actuators of ants were modeled and the efficiency of the connectionist approach has been validated by the comparison with a simple symbolical approach. Apart from several surprising results on technical details, which are reported, the present approach clearly demonstrates the feasibility of such an implementation with connectionist and biologically more plausible principles, offering promising perspectives as a basis for further artificial life systems.

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Author information

Authors and Affiliations

  1. Institut für Algorithmen und Kognitive Systeme (IAKS), Universität Fridericiana zu Karlsruhe (TH), Am Fasanengarten 5, 76131, Karlsruhe, Germany

    Marvin Oliver Schneider

  2. Centro de Ciências Exatas, Ambientais e de Tecnologias (Ceatec), Pontifical Catholic University of Campinas, Rodovia D. Pedro I, km 136, Campinas-São Paulo, 13012-970, Brazil

    João Luís Garcia Rosa

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  1. Marvin Oliver Schneider
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  2. João Luís Garcia Rosa
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Correspondence to Marvin Oliver Schneider.

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Schneider, M.O., Rosa, J.L.G. Application and development of biologically plausible neural networks in a multiagent artificial life system. Neural Comput & Applic 18, 65–75 (2009). https://doi.org/10.1007/s00521-007-0156-0

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