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An account of grammatical acquisition is developed within the parametersetting framework applied to a generalized categorial grammar (GCG). The GCG is embedded in a default inheritance network yielding a natural partial ordering (reflecting generality) of parameters which determines a partial order for parameter setting. Computational simulation shows that several resulting acquisition procedures are effective on a parameter set expressing major typological distinctions based on constituent order, and defining 70 distinct full languages and over 200 subset languages. The effects on acquisition of inductive bias, that is, of differing initial parameter settings, are explored via computational simulation. Computational simulation of populations of language learners and users instantiating the acquisition model show: 1) that variant acquisition procedures, with differing inductive biases, exert differing selective pressures on the evolution of language(s); 2) acquisition proc...

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Gender gaps may be observed in a variety of economic and social environments. One of the possible determining factors is that men are more competitive than women and so, when the competitiveness of the environment increases, the performance of men increases relative to that of women. We test this hypothesis in a field study conducted with 9-year old children, running on a track. They first run alone and then in pairs over a short distance with different gender composition of the pairs. The results support the hypothesis that performance in competition varies according to gender. When children ran alone, there was no difference in performance. In competition boys, but not girls, improved their performance. This finding relates to the discussion regarding single sex schools: the outcomes of examinations in a mixed sex school can show a gender gap in favor of boys, even when this gap does not reflect actual abilities. Girls who are as talented as boys will end up performing worse just because they are not as competitive, and will not achieve as high scores in examinations as boys.

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This research develops an evolutionary growth theory that captures the interplay between the evolution of mankind and economic growth since the emergence of the human species. This uni¯ed theory encompasses the observed evolution of population, technology and income per capita in the long transition from an epoch of Malthusian stagnation to sustained economic growth. The theory suggests that prolonged economic stagnation prior to the transition to sustained growth stimulated natural selection that shaped the evolution of the human species, whereas the evolution of the human species was the origin of the take-o ® from an epoch of stagnation to sustained growth.

The most successful, complex, and numerous species on earth are composed of sexuallyreproducing animals and flowering plants. Both groups typically undergo a form of sexual selection through mate choice: animals are selected by conspecifics and flowering plants are selected by heterospecific pollinators. This suggests that the evolution of phenotypic complexity and diversity may be driven not simply by natural-selective adaptation to econiches, but by subtle interactions between natural selection and sexual selection. This paper reviews several theoretical arguments and simulation results in support of this view. Biological interest in sexual selection has exploded in the last 15 years (see Andersson & Bradbury, 1987; Cronin, 1991), but has not yet been integrated with the biocomputational perspective on evolution as a process of search and optimization (Holland, 1975; Goldberg, 1989). In the terminology of sexual selection theory, mate preferences for "viability indicators" (e.g. Hami...

This article reports on the current state of our efforts to shed light on the origin and evolution of linguistic diversity using synthetic modeling and arti#cial life techniques. We construct a simple abstract model of a communication system that has been designed with regard to referential signaling in nonhuman animals. We analyze the evolutionary dynamics of vocabulary sharing based on these experiments. The results show that mutation rates, population size, and resource restrictions de#ne the classes of vocabulary sharing. We also see a dynamic equilibrium, where two states, a state with one dominant shared word and a state with several dominant shared words, take turns appearing. We incorporate the idea of the abstract model into a more concrete situation and present an agent-based model to verify the results of the abstract model and to examine the possibility of using linguistic diversity in the #eld of distributed AI and robotics. It has been shown that the evolution of linguistic diversity in vocabulary sharing will support cooperative behavior in a population of agents.

Communication signals in many animal species (including humans) show a surprising amount of variety both across time and at any one instant in a population. Traditional accounts and simulation models of the evolution of communication offer little explanation of this diversity. Sexual selection of signals used to attract mates, and the coevolving preferences used to judge those signals, can instead provide a convincing mechanism. Here we demonstrate that a wide variety of "songs" can evolve when male organisms sing their songs to females who judge each male's output and decide whether or not to mate with him based on their own coevolved aesthetics. Evolved variety and rate of innovation are greatest when females combine inherited song preferences with a desire to be surprised. If females choose mates from a small pool of candidates, diversity and rate of change are also increased. Such diversity of communication signals may have implications for the evolution of brai...