Language Evolution and Computation Bibliography

This paper investigates the interaction between cultural evolution and biological evolution in the emergence of phonemic coding in speech. It is observed that our nearest relatives, the primates, use holistic utterances, whereas humans use phonemic utterances. It can therefore be argued that our last common ancestor used holistic utterances and that these must have evolved into phonemic utterances. This involves co-evolution between a repertoire of speech sounds and adaptations to using phonemic speech. The culturally transmitted system of speech sounds influences the fitness of the agents and could conceivably block the transition from holistic to phonemic speech. This paper investigates this transition using a computer model in which agents that can either use holistic or phonemic utterances co-evolve with a lexicon of words. The lexicon is adapted by the speakers to conform to their preferences. It is shown that although the dynamics of the transition are changed, the population still ends up of agents that use phonemic speech.

The complexity, variation, and change of languages make evident the importance of representation and learning in the acquisition and evolution of language. For example, analytic studies of simple language in unstructured populations have shown complex dynamics, depending on the fidelity of language transmission. In this study we extend these analysis of evolutionary dynamics to include grammars inspired by the principles and parameters paradigm. In particular, the space of languages is structured so that some pairs of languages are more similar than others, and mutations tend to change languages to nearby variants. We found that coherence emerges with lower learning fidelity than predicted by earlier work with an unstructured language space.

This paper presents a computational framework for studying the influence of learning on the evolution of avian communication. We conducted computer simulations for exploring the effects of different learning strategies on the evolution of bird song. Experimental results show the genetic assimilation of song repertoires as a consequence of interactions between learning and evolution.

Typically, multi-agent models for studying the evolution of perceptually grounded lexicons assume that agents perceive the same set of objects, and that there is either joint attention, corrective feedback or cross-situational learning. In this paper we address these two assumptions, by introducing a new multi-agent model for the evolution of perceptually grounded lexicons, where agents do not perceive the same set of objects, and where agents receive a cue to focus their attention to objects, thus simulating a Theory of Mind. In addition, we vary the amount of corrective feedback provided to guide learning word-meanings. Results of simulations show that the proposed model is quite robust to the strength of these cues and the amount of feedback received.