The evolutionary dynamics of language.

The well-established framework of evolutionary dynamics can be applied to the fascinating open problems how human brains are able to acquire and adapt language and how languages change in a population. Schemas for handling grammatical constructions are the replicating unit. They emerge and multiply with variation in the brains of individuals and undergo selection based on their contribution to needed expressive power, communicative success and the reduction of cognitive effort.

Human language is a culturally evolving system.

It is well accepted that languages change rapidly in a process of cultural evolution. But some animal communication systems, in particular bird song, also exhibit cultural change. So where exactly is the difference? This article argues that the main selectionist pressure on human languages is not biological-that is, related to survival and fecundity-but instead is linked to producing enough expressive power for the needs of the community, maximizing communicative success, and reducing cognitive effort.

Agent-based models for the emergence and evolution of grammar.

Human languages are extraordinarily complex adaptive systems. They feature intricate hierarchical sound structures, are able to express elaborate meanings and use sophisticated syntactic and semantic structures to relate sound to meaning. What are the cognitive mechanisms that speakers and listeners need to create and sustain such a remarkable system? What is the collective evolutionary dynamics that allows a language to self-organize, become more complex and adapt to changing challenges in expressive power? This paper focuses on grammar.

Agent-based models of strategies for the emergence and evolution of grammatical agreement.

Grammatical agreement means that features associated with one linguistic unit (for example number or gender) become associated with another unit and then possibly overtly expressed, typically with morphological markers. It is one of the key mechanisms used in many languages to show that certain linguistic units within an utterance grammatically depend on each other. Agreement systems are puzzling because they can be highly complex in terms of what features they use and how they are expressed.

Interactions between cultural, social and biological explanations for language evolution.

This is a reply to commentaries on a target article in this volume reviewing models for the cultural evolution of language. Many commentaries amplify positions taken in this article but they also cover novel issues in social evolution and biological evolution, which are briefly addressed here.

Modeling the cultural evolution of language.

The paper surveys recent research on language evolution, focusing in particular on models of cultural evolution and how they are being developed and tested using agent-based computational simulations and robotic experiments. The key challenges for evolutionary theories of language are outlined and some example results are discussed, highlighting models explaining how linguistic conventions get shared, how conceptual frameworks get coordinated through language, and how hierarchical structure could emerge. The main conclusion of the paper is that cultural evolution is a much more powerful process that usually assumed, implying that less innate structures or biases are required and consequently that human language evolution has to rely less on genetic evolution.

The methodology of the artificial.

Biorobotics research should not only target "realistic" models of living systems and be judged exclusively from that perspective. It should pay just as much attention to formal models and artificial systems. They allow the examination of assumptions which do not necessarily hold for living systems, but precisely therein lies their value.

Experiments on the emergence of human communication.

Children learn language from their parents and then use the acquired system throughout the rest of their life with little change. At least that is commonly assumed. But a recent paper by Galantucci adds to the growing evidence that adults (and children) are able to create and negotiate complex communication systems from scratch and relatively quickly, without a prior model.

Coordinating perceptually grounded categories through language: a case study for colour.

This article proposes a number of models to examine through which mechanisms 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.

Intelligence with representation.

Behaviour-based robotics has always been inspired by earlier cybernetics work such as that of W. Grey Walter. It emphasizes that intelligence can be achieved without the kinds of representations common in symbolic AI systems.

Evolving grounded communication for robots.

The computational and robotic synthesis of language evolution is emerging as a new exciting field of research. The objective is to come up with precise operational models of how communities of agents, equipped with a cognitive apparatus, a sensori-motor system, and a body, can arrive at shared grounded communication systems. Such systems may have similar characteristics to animal communication or human language.