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

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. [ABSTRACT FROM AUTHOR]