GATSBY COMPUTATIONAL NEUROSCIENCE UNIT
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Larry Yaeger

Indiana University, USA

 

Wednesday 9 July 2008

16.00

Seminar Room B10 (Basement)

Alexandra House, 17 Queen Square, London, WC1N 3AR

 

Trends in the Evolution of Neural Complexity

 

The nature and source of evolutionary trends in complexity is difficult to assess from the fossil record, and the driven vs. passive nature of such trends has been debated for decades.  There are also questions about how effectively artificial life software can evolve increasing levels of complexity.  Having previously demonstrated an evolutionary increase in an information theoretic measure of neural complexity in an artificial life system (Polyworld), I extend the work by introducing a technique for distinguishing driven from passive trends in complexity.  Experiments show that evolution can and does select for complexity increases in a driven fashion in some circumstances, but under other conditions it can select for complexity stability, or even complexity reduction.  It is suggested that the evolution of complexity is entirely driven--just not in a single direction--at the scale of species.  Large scale trends may appear random as a result of the integration of these conflicting small scale trends, but increasing "eco-space" may produce large scale driven trends in complexity.