论文信息 - A simple genetic algorithm for reducible complexity

A simple genetic algorithm for reducible complexity

Challenges are often lofted to explain how gradualistic evolution can evolve systems where function ceases with the removal of any of their multiple parts. We present a genetic algorithm (GA) example using a dynamic fitness function. Given clear definitions of relevant terms, the GA produces such complex systems.

Steffen Christensen | Lee K. Graham | Franz Oppacher

[1] Lee K. Graham,et al. Speciation through Exaptation , 2007, 2007 IEEE Symposium on Artificial Life.

[2] R. Dawkins. The Blind Watchmaker , 1986 .

[3] Robert T. Pennock,et al. The evolutionary origin of complex features , 2003, Nature.

[4] W. Daniel Hillis,et al. Co-evolving parasites improve simulated evolution as an optimization procedure , 1990 .

[5] Jason Noble,et al. The origins of mimicry rings , 2002 .

[6] Joseph E. Boxhorn. Observed Instances of Speciation , 2004 .

[7] David H. Ackley,et al. Interactions between learning and evolution , 1991 .

[8] J. Pollack,et al. Challenges in coevolutionary learning: arms-race dynamics, open-endedness, and medicocre stable states , 1998 .

[9] S. Gould,et al. Exaptation—a Missing Term in the Science of Form , 1982, Paleobiology.

[10] Geoffrey E. Hinton,et al. How Learning Can Guide Evolution , 1996, Complex Syst..

[11] J. Baldwin. A New Factor in Evolution , 1896, The American Naturalist.