title: Development of a spin-glass model of prebiotic evolution: environmental effects on ensembles of genetic polymers.
abstract: We develop in two ways an existing spin-glass model of prebiotic polymer evolution. First, by choosing the environment J in a prescribed manner, similar to neural network presciptions, we may create an environment which favors a linearly independent set of evolutionary niches (Ea). That is, we may control which polymer "species" will evolve in our system. Computer simulations confirm this result. We obtain a quantitative value for the sharpness of a niche. Second, we extend the model by allowing a surviving polymer to act upon--to "remold"--its environment; the nature of the environmental action is governed by the "molding" matrix M. When the mold M is the identity matrix, the feedback algorithm reduces to a Hebb learning algorithm form, and a surviving polymer acts to enhance its own survival prospects. Molds having a structure analogous to (temporal) associative memories in neural networks can generate autocatalytic species or can exhibit symbiotic interspecies relationships.
authors: Joseph Henry Laboratories of Physics, Princeton University, NJ 08544.
authors: A J
authors: AJ
authors: Wong
mesh_terms: D005075:Biological Evolution; D003198:Computer Simulation; D005815:Genetic Code; D008433:Mathematics; D008957:Models, Genetic; D011108:Polymers
chemical_list: D011108:Polymers