tech rep available on evolving neural networks

[Dr Michael G Dyer]

Evolution of Communication in Artificial Organisms*

Gregory M. Werner
Michael G. Dyer

Tech. Rep. UCLA-AI-90-06

Abstract:  A population of artificial organisms evolved simple 
communication protocols for mate finding.  Female animals in our 
artificial environment had the ability to see males and to emit sounds. 
Male animals were blind, but could hear signals from females.  Thus, the 
environment was designed to favor organisms that evolved to generate and 
interpret meaningful signals.  Starting with random neural networks, the 
simulation resulted in a progression of generations that exhibit 
increasingly effective mate finding strategies.  In addition, a number 
of distinct subspecies, i.e. groups with different signaling protocols 
or "dialects", evolve and compete.  These protocols become a behavioral 
barrier to mating that supports the formation of distinct subspecies.  
Experiments with physical barriers in the environment were also 
performed.  A partially permeable barrier allows a separate subspecies 
to evolve and survive for indefinite periods of time, in spite of 
occasional migration and contact from members of other subspecies.

* To appear in: J. D. Farmer, C. Langton, S. Rasmussen & C. Taylor 
(Eds.),  Artificial Life II, Addison-Wesley, in press.

For a copy of the above paper, please send a request for Tech. Rep. 
UCLA-AI-90-06   to:   valerie at cs.ucla.edu