Computer Science – Neural and Evolutionary Computing
Scientific paper
2011-12-21
Computer Science
Neural and Evolutionary Computing
8 pages; In Bullock, S. et al. eds. Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation
Scientific paper
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. We extend our previous work demonstrating an evolutionary increase in an information theoretic measure of neural complexity in an artificial life system (Polyworld), and introduce a new technique for distinguishing driven from passive trends in complexity. Our experiments show that evolution can and does select for complexity increases in a driven fashion, in some circumstances, but under other conditions it can also select for complexity stability. It is suggested that the evolution of complexity is entirely driven---just not in a single direction---at the scale of species. This leaves open the question of evolutionary trends at larger scales.
Griffith Virgil
Sporns Olaf
Yaeger Larry
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