Naming Game on Adaptive Weighted Networks

We examine a naming game on an adaptive weighted network. A weight of connection for a given pair of agents depends on their communication success rate and determines the probability with which the agents communicate. In some cases, depending on the parameters of the model, the preference toward successfully communicating agents is basically negligible and the model behaves similarly to the naming game on a complete graph. In particular, it quickly reaches a single-language state, albeit some details of the dynamics are different from the complete-graph version. In some other cases, the preference toward successfully communicating agents becomes much more relevant and the model gets trapped in a multi-language regime. In this case gradual coarsening and extinction of languages lead to the emergence of a dominant language, albeit with some other languages still being present. A comparison of distribution of languages in our model and in the human population is discussed.Comment: 22 pages, accepted in Artificial Lif

Language structure in the n-object naming game

We examine a naming game with two agents trying to establish a common vocabulary for n objects. Such efforts lead to the emergence of language that allows for an efficient communication and exhibits some degree of homonymy and synonymy. Although homonymy reduces the communication efficiency, it seems to be a dynamical trap that persists for a long, and perhaps indefinite, time. On the other hand, synonymy does not reduce the efficiency of communication, but appears to be only a transient feature of the language. Thus, in our model the role of synonymy decreases and in the long-time limit it becomes negligible. A similar rareness of synonymy is observed in present natural languages. The role of noise, that distorts the communicated words, is also examined. Although, in general, the noise reduces the communication efficiency, it also regroups the words so that they are more evenly distributed within the available "verbal" space.Comment: minor change

The evolution of language: a comparative review

For many years the evolution of language has been seen as a disreputable topic, mired in fanciful "just so stories" about language origins. However, in the last decade a new synthesis of modern linguistics, cognitive neuroscience and neo-Darwinian evolutionary theory has begun to make important contributions to our understanding of the biology and evolution of language. I review some of this recent progress, focusing on the value of the comparative method, which uses data from animal species to draw inferences about language evolution. Discussing speech first, I show how data concerning a wide variety of species, from monkeys to birds, can increase our understanding of the anatomical and neural mechanisms underlying human spoken language, and how bird and whale song provide insights into the ultimate evolutionary function of language. I discuss the ‘‘descended larynx’ ’ of humans, a peculiar adaptation for speech that has received much attention in the past, which despite earlier claims is not uniquely human. Then I will turn to the neural mechanisms underlying spoken language, pointing out the difficulties animals apparently experience in perceiving hierarchical structure in sounds, and stressing the importance of vocal imitation in the evolution of a spoken language. Turning to ultimate function, I suggest that communication among kin (especially between parents and offspring) played a crucial but neglected role in driving language evolution. Finally, I briefly discuss phylogeny, discussing hypotheses that offer plausible routes to human language from a non-linguistic chimp-like ancestor. I conclude that comparative data from living animals will be key to developing a richer, more interdisciplinary understanding of our most distinctively human trait: language

Cultural transmission and biological markets

Active cultural transmission of fitness-enhancing behavior (sometimes called “teaching”) can be seen as a costly strategy: one for which its evolutionary stability poses a Darwinian puzzle. In this article, we offer a biological market model of cultural transmission that substitutes or complements existing kin selection-based proposals for the evolution of cultural capacities. We explicitly demonstrate how a biological market can account for the evolution of teaching when individual learners are the exclusive focus of social learning (such as in a fast-changing environment). We also show how this biological market can affect the dynamics of cumulative culture. The model works best when it is difficult to have access to the observation of the behavior without the help of the actor. However, in contrast to previous non-mathematical hypotheses for the evolution of teaching, we show how teaching evolves even when innovations are insufficiently opaque and therefore vulnerable to acquisition by emulators via inadvertent transmission. Furthermore, teaching in a biological market is an important precondition for enhancing individual learning abilitie

Review of: The evolution of human language: Biolinguistic perspectives (R. Larson et al., CUP, 2010)

International audience<p>Where does human language come from? The ‘greatest problem in science’, according to Bickerton (2009), remains a mystery. This new volume offers a partial but important map of current ideas on the problem. The book is stimulating because of the issues it raises and surprising in the issues it ignores.</p