%0 Book %1 kauffman_1995 %A Kauffman, Stuart A. %C Oxford, UK %D 1995 %I OUP %K complexity evolution %T At Home in the Universe: The Search for the Laws of Self-Organization and Complexity %U http://www.amazon.com/At-Home-Universe-Self-Organization-Complexity/dp/0195095995/ref=ed_oe_h/104-7655899-5779117?ie=UTF8

@book{kauffman_1995, added-at = {2009-01-02T17:19:33.000+0100}, address = {Oxford, UK}, author = {Kauffman, Stuart A.}, biburl = {https://www.bibsonomy.org/bibtex/2a7903d8f9ed4115c276d71e1ed482266/sccook}, citeulike-article-id = {827953}, comment = {- p.27 evolutionary spaces are most dynamic when at the boundary of order and chaos, as populations shift from local peaks and flow to other regions - p 170 introduces the NK fitness landscape model. It models the effect various gene alleles have on each other using a binary model. N is some allele, and K is other genes which are assigned to it (randomly, in most cases). Therefore the total fitness contribution of allele N is 2^(k+1). Each combination is assigned a value for contribution to fitness for the genotype. The advantage is being able to iterate through contributions and assess relative fitness for certain permutations of fitness values. The overall fitness is the contribution of each N gene, divided by the number of genes. - the NK model asserts the interconnected nature of genotypes, explicitly showing the relationships (in a network model). K measures interconnectedness, and higher K means more rugged fitness landscapes. - a fitness landscape represents replication rate of a geno/phenotype. This is the y-axis; the x-axis is a list of possible genotypes, I believe related by similarity, e.g. blue eyes and grey eyes would be adjacent (and possibly of equal replication rate). I still don't understand where the environment comes into play here. Surely the replication rate is a product of the genotype and the environment. - "[compared to blind watchmaker] ... I suspect that much of technological evolution results from tinkering with little real understanding ahead of time of the consequences... when problems are hard, thinking may not help that much" p. 202 - learning curves, diminishing returns p 203 - is there a central directing agency e.g. DNA or just self-organization in the large? p.274 - LISP evolution and level-0 -- simple propagators vs level-1 -- self-replicating/sustaining organisms p. 279 - memes}, interhash = {0b6c603b97f4454b4b620fe2d6d2cbf1}, intrahash = {a7903d8f9ed4115c276d71e1ed482266}, keywords = {complexity evolution}, priority = {0}, publisher = {OUP}, timestamp = {2009-01-02T17:19:33.000+0100}, title = {At Home in the Universe: The Search for the Laws of Self-Organization and Complexity}, url = {http://www.amazon.com/At-Home-Universe-Self-Organization-Complexity/dp/0195095995/ref=ed_oe_h/104-7655899-5779117?ie=UTF8}, year = 1995 }