Chaos as a source of complexity and diversity in evolution

The relevance of chaos to evolution is discussed in the context of the origin and maintenance of diversity and complexity. Evolution to the edge of chaos is demonstrated in an imitation game. As an origin of diversity, dynamic clustering of identical chaotic elements, globally coupled each to the other, is briefly reviewed. The clustering is extended to nonlinear dynamics on hypercubic lattices, which enables us to construct a self-organizing genetic algorithm. A mechanism of maintenance of diversity, “homeochaos,” is given in an ecological system with interaction among many species. Homeochaos provides a dynamic stability sustained by high-dimensional weak chaos. A novel mechanism of cell differentiation is presented, based on dynamic clustering. Here, a new concept—“open chaos”—is proposed for the instability in a dynamical system with growing degrees of freedom. It is suggested that studies based on interacting chaotic elements can replace both top-down and bottom-up approaches.

[1]  Young,et al.  Inferring statistical complexity. , 1989, Physical review letters.

[2]  Kunihiko Kaneko Junji Suzuki,et al.  Imitation games , 1993, adap-org/9311002.

[3]  K. Kaneko,et al.  Cell division, differentiation and dynamic clustering , 1993, adap-org/9311001.

[4]  K. Kaneko.  Pattern dynamics in spatiotemporal chaos: Pattern selection, diffusion of defect and pattern competition intermettency , 1989 .

[5]  Kunihiko Kaneko,et al.  Evolution to the Edge of Chaos in Imitation Game , 1993 .

[6]  R. May,et al.  Stability and Complexity in Model Ecosystems , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  M. Kimura,et al.  The neutral theory of molecular evolution. , 1983, Scientific American.

[8]  Grégoire Nicolis,et al.  Self-Organization in nonequilibrium systems , 1977 .

[9]  Ichiro Tsuda.  Chaotic Neural Networks and Thesaurus , 1991 .

[10]  Clive K. Catchpole,et al.  Vocal communication in birds , 1979 .

[11]  K. Ikeda,et al.  Maxwell-Bloch Turbulence , 1989 .

[12]  T. Ikegami,et al.  Evolution of host-parasitoid network through homeochaotic dynamics. , 1992, Chaos.

[13]  M. Eigen,et al.  Molecular quasi-species. , 1988 .

[14]  Christopher G. Langton,et al.  Computation at the edge of chaos: Phase transitions and emergent computation , 1990 .

[15]  Michael F. Shlesinger,et al.  Dynamic patterns in complex systems , 1988 .

[16]  Kunihiko Kaneko.  Erratum: Chaotic but regular posi-nega switch among coded attractors by cluster-size variation [Phys , 1989 .

[17]  D. Hofstadter,et al.  Godel, Escher, Bach: An Eternal Golden Braid , 1979 .

[18]  S. Kauffman,et al.  Coevolution to the edge of chaos: coupled fitness landscapes, poised states, and coevolutionary avalanches. , 1991, Journal of theoretical biology.

[19]  R. Lord,et al.  The Pattern of Animal Communities , 1967 .

[20]  J. Krebs,et al.  Song repertoires and territory defence in the great tit , 1978, Nature.

[21]  Tetsuya Yomo,et al.  Dynamic clustering of bacterial population , 1994 .

[22]  L. Buss,et al.  The evolution of individuality , 1987 .

[23]  T. Ikegami,et al.  Homeochaos: dynamic stability of a symbiotic network with population dynamics and evolving mutation rates , 1992 .

[24]  P. Grassberger.  Toward a quantitative theory of self-generated complexity , 1986 .

[25]  Kaneko,et al.  Globally coupled chaos violates the law of large numbers but not the central-limit theorem. , 1990, Physical review letters.