The paper proposes a number of models to examine through what mech-anisms a population of autonomous agents could arrive at a repertoire of perceptually grounded categories that is sufficiently shared to allow successful communication. The models are inspired by the main approaches to human categorisation being discussed in the literature: nativism, empiricism, and culturalism. Colour is taken as a case study. Although the paper takes no stance on which position is to be accepted as final truth with respect to hu-man categorisation and naming, it points to theoretical constraints that make each position more or less likely and contains clear suggestions on what the best engineering solution would be. Specifically, it argues that the collective choice of a shared repertoire must integrate multiple constraints, including constraints coming from communication.

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...

An account of parameter setting during grammatical acquisition is presented in terms of Generalized Categorial Grammar embedded in a multiple default inheritance hierarchy, providing a natural partial ordering on the setting of parameters (Briscoe, 1997a). Experiments reported show that several experimentally effective learners can be defined in this framework capable of reliably acquiring a grammar from a sequence of triggers drawn from one of 70 full languages (or the 200+ more restricted subset languages of these full languages). Evolutionary computational simulations of evolving populations of such language learners/users suggest that: 1) languages evolve towards greater learnability, interpretability and/or expressivity; 2) learning procedures evolve towards more efficient variants depending on the linguistic environment of adaptation. The reciprocal evolution of language learning procedures and of language creates a genuinely coevolutionary dynamic, despite the relative speed of ...

In this paper we describe the application of a so called "Self-Generating" Memetic Algorithm to the Maximum Contact Map Overlap problem (MAX-CMO). The maximum overlap of contact maps is emerging as a leading modeling technique to obtain structural alignment among pairs of protein structures. Identifying structural alignments (and hence similarity among proteins) is essential to the correct assessment of the relation between proteins structure and function. A robust methodology for structural comparison could have impact on the process of rational drug design.

It has been postulated that aspects of human language are both genetically and culturally transmitted. How might these processes interact to determine the structure of language? An agent-based model designed to study gene-culture interactions in the evolution of communication is introduced. This model shows that cultural selection resulting from learner biases can be crucial in determining the structure of communication systems transmitted through both genetic and cultural processes. Furthermore, the learning bias which leads to the emergence of optimal communication in the model resembles the learning bias brought to the task of communication by human infants. This suggests that the iterated application of such human learning biases may explain much of the structure of human language.

In this paper we examine the effects of the emergence of a new replicator, memes, on the evolution of a pre-existing replicator, genes. Using a version of the NKCS model we examine the effects of increasing the rate of meme evolution in relation to the rate of gene evolution, for various degrees of interdependence between the two replicators. That is, the effects of memes' (suggested) more rapid rate of evolution in comparison to that of genes is investigated using a tunable model of coevolution. It is found that, for almost any degree of interdependence between the two replicators, as the rate of meme evolution increases, a phase transition-like dynamic occurs under which memes have a significantly detrimental effect on the evolution of genes, quickly resulting in the cessation of effective gene evolution. Conversely, the memes experience a sharp increase in benefit from increasing their rate of evolution. We then examine the effects of enabling genes to reduce the percentage of gene-detrimental evolutionary steps taken by memes. Here a critical region emerges as the comparative rate of meme evolution increases, such that if genes cannot effectively select memes a high percentage of the time, they suffer from meme evolution as if they had almost no selective capability. 2 1.

‘Racial’ disparities among cancers, particularly of the breast and prostate, are something of a mystery. For the US, in the face of slavery and its sequelae, centuries of interbreeding has greatly leavened genetic differences between ‘Blacks ’ and ‘whites’, but marked contrasts in disease prevalence and progression persist. ‘Adjustment’ for socioeconomic status and lifestyle, while statistically accounting for much of the variance in breast cancer, only begs the question of ultimate causality. Here we propose a more basic biological explanation that

Extending recent information-theoretic phase transition approaches to evolutionary and cognitive process via the Rate Distortion Theorem in the circumstance of interaction with a structured environment suggests that learning plateaus in cognitive systems and punctuated equilibria in evolutionary process are formally analogous, even though evolution is most certainly not cognitive. The result is curiously direct, and implies that evolutionary theories which do not produce punctuation are likely to be seriously incomplete.

In this paper, I review arguments for and against the emergence and maintenance of an innate language acquisition device (LAD) via genetic assimilation. By a LAD, I mean nothing more or less than a learning mechanism which incorporates

Introduction 1.1 Human sociality in comparative perspective E.O. Wilson (1975) described humans as one of the four pinnacles of social evolution. The other pinnacles are the colonial invertebrates, the social insects, and the non-human mammals. Wilson separated human sociality from that of the rest of the mammals because, with the exception of the social insect like Naked Mole Rats, only humans have generated societies of a grade of complexity that approaches that of the social insects and colonial invertebrates. In the last few millennia, human societies have even begun to exceed, in numbers of individuals and degree of complexity, the societies of ants, termites, and corals. Human social complexity is based on quite different principles than the ultra-sociality of any other species. In all other known cases, the constituent individuals of societies are either genetically identical, as in the colonial invertebrates, or closely related, as in the social insects and no