Evolution and Biocomputation: Computational Models of by Wolfgang Banzhaf, Frank H. Eeckman

By Wolfgang Banzhaf, Frank H. Eeckman

This quantity includes ten completely refereed and revised complete papers originating from an interdisciplinary workshop on biocomputation entitled "Evolution as a Computational Process", held in Monterey, California in July 1992. This ebook is dedicated to viewing organic evolution as a massive computational procedure being performed over an enormous spatial and temporal scale. desktop scientists, mathematicians and physicists may perhaps know about optimization from taking a look at usual evolution and biologists may perhaps know about evolution from learning man made existence, online game idea, and mathematical optimization. as well as the 10 complete papers addressing e.g. inhabitants genetics, emergence, man made lifestyles, self-organization, evolutionary algorithms, and choice, there's an introductory survey and a topic index.

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Example text

To simplify the model, we have first supposed that the host A offers only one site where E or D are able to bind. This simplification limits the set of possible associations to couples AD and AE. Changes in population sizes are due to elementary processes represented in Figure 2. Those elementary processes are: reproduction which depends on a fitness 32 coefficient, death which occurs with a rate d, mutation which occurs with a rate m and association and dissociation which depend on kinetic constants.

7) of the simplified dynamical system are the same for both models (single site and multi-site, resp. SSM and MSM). For the MSM the first three equations are written: kse-AE = kie. 11), in x and y as in the SSM. 11) is equivalent in SSM to equation (5. 3) when one notices that the free A population of the SSM corresponds to the number of free sites in A, pA-AD-AE, of the MSM. fl in the SSM then corresponds to f l in the MSM. P P Since the dynamical equations on the slow manifold are the same in both models, we expect the attractors and their domains of existence to be the same, which is verified by the computer simulations.

T i # t'~'# 7 II I| / I I I I / f A I I ',/I I FF 11 / I 0 1 e I q O~F --- I 1 I I 11 Ii II -I '1. Fig. 2: Set of the elementary processes that modify the populations. Thin continuous lines represent fast association processes between hosts and guests organisms with kinetic constants kl d, kl e, and fast dissociation processes with kinetic constants ks d and ks e. Bold lines represent reproduction and death processes (with rate d). The greek letters represent the fitness coefficients associated with the reproduction processes of the organisms.

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