Using computer simulations I studied the simultaneous effect of variable environments, mutation rates, ploidy, number of loci subject to evolution and random and assortative mating on various reproductive systems. The simulations showed that mutants for sex and recombination are evolutionarily stable, displacing alleles for monosexuality in diploid populations mating assortatively under variable selection pressure. Assortative mating reduced excessive allelic variance induced by recombination and sex, especially among diploids. Results suggest a novel adaptive value for sex and recombination. They show that (...) the adaptive value of diploidy and that of the segregation of sexes is different to that of sex and recombination. The results suggest that the emergence of sex had to be preceded by the emergence of diploid monosexual organisms and provide an explanation for the emergence and maintenance of sex among diploids and for the scarcity of sex among haploid organisms. (shrink)

Results of an agent-based computer simulation of the evolution of diploid sexual organisms showed that several mate selection strategies confer much higher average fitness to the simulated populations, and higher evolutionary stability to the alleles coding for these strategies, than random mating. Strategies which select for ''good genes'' were very successful, and so were strategies based on assortative mating. The results support the hypothesis that mating is not likely to be random in nature and that the most successful mate selection (...) strategies are those based on assortative mating or on advantageous genes. (shrink)

Advances in multiagent simulation techniques make it possible to study more realistic dynamics of complex systems and allow evolutionary theories to be tested. Here I use simulations to assess the relative importance of reproductive systems (haplodiploidy vs. diploidy), mate selection (assortative mating vs. random mating) and social economics (pay-off matrices of evolutionary games) in the evolutionary dynamics leading to the emergence of social cooperation in the provision of parental care. The simulations confirm that haplo-diploid organisms and organisms mating assortatively have (...) a higher probability for fixing alleles and require less favorable conditions for their fixation, than diploids or organisms mating randomly. The simulations showed that social behavior was most likely to emerge a) when the cost for parental investment was much lower than the benefits to the offspring, b) when cooperation improved synergistically the fitness of offspring compared to the corresponding egoistic behavior and c) when alleles coding for altruistic or social behavior could be rapidly fixed in the population, thanks to mechanisms such as haplo-diploidy and/or assortative mating. Cooperative social behavior always appeared if sociality conferred much higher fitness gains compared to non cooperative alternatives suggesting that the most important factors for the emergence and maintenance of social behavior are those based on energetic or efficiency considerations. The simulations, in congruence with the scant experimental evidence available, suggest that economic considerations rather than genetic ones are critical in explaining the emergence and maintenance of sociality. (shrink)

The concept of altruism is used in very different forms by computer scientists,economists, philosophers, social scientists, psychologists and biologists. Yet, in order to be useful in social simulations, the concept altruism requires a more precise meaning. A quantitative formulation is proposed here, based on the cost/benefit analysis of the altruist and of society at large. This formulation is applied in the analysis of the social dynamic working of behaviors that have been called altruistic punishments, using the agent based computer model (...) Sociodynamica. The simulations suggest that altruistic punishment on its own cannot maintain altruistic behaviors. Altruistic behavior is sustainable in the long term only if these behaviors trigger synergetic forces in society that eventually make them produce benefits to most individuals. The simulations suggest however that altruistic punishment may work as a social investment , and is thus better called decentralized social punishment. This behavior is very efficient in enforcing social norms. The efficiency of decentralized social punishment in enforcing norms was dependent on the type of labor structured of the virtual society. I conclude that what is called altruistic punishment emerges as a type of social investment that can evolve either through individual and/or group selection, as a successful device for changing or enforcing norms in a society. Social simulations will help us in better understanding the underlying dynamic working of such devices. (shrink)