this paper, we show that the co-occurrence of words in sentences relies on the network structure of the lexicon, the properties of which are analysed in depth. As we will show in this paper, human language can be described in terms of a graph of word interactions. This graph has some unexpected properties (shared by other biological and technological networks (Amaral et al. 2000; Strogatz 2001)) that might underlie its diversity and exibility, and create new questions about its origins and organization

Abstract. This paper proposes cognitive developmental robotics as a new principle for the design of humanoid robots. This principle may provide ways of understanding human beings that go beyond the current level of explanation found in the natural and social sciences. Furthermore, a methodological emphasis on humanoid robots in the design of artificial creatures holds promise because they have many degrees of freedom and sense modalities and, thus, must face the challenges of scalability that are often side stepped in simpler domains. We examine the potential of this new principle as well as issues that are likely to be important to CDR in the future. 1

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...

The paper discusses efforts to understand the self-organisation and evolution of language from a cognitive modeling point of view. It focuses in particular on efforts that use connectionist components to synthesise some of the major stages in the emergence of language and possible transitions between stages. The paper does not introduce new technical results but discusses a number of dimensions for mapping out the research landscape. 1 1

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 ...

Properties of the physical world have shaped human evolutionary design and given rise to physically grounded mental representations. These grounded representations provide the foundation for higher level cognitive processes including language. Most natural language processing machines to date lack grounding. This paper advocates the creation of physically grounded language learning machines as a path toward scalable systems which can conceptualize and communicate about the world in human-like ways. As steps in this direction, two experimental language acquisition systems are presented.

The main purpose of this article is to argue the merits of ‘population thinking’ in gaining insight into linguistic and, in particular, syntactic change. Population-level thinking and modelling can shed new light on many issues in the study of language acquisition and language change, and leads directly to a precise and useful characterisation of E-language. Something which is lacking in current generative linguistics. Moreover, this way of thinking is fully compatible with the major insights of the latter, and integrates them into a framework in which language variation and change are inherent and inevitable, rather than peripheral and/or accidental, properties of language. I will argue that (E-)languages are best modelled as particular kinds of dynamical systems; namely, complex adaptive systems (where these terms are used in technical senses made precise below). The article both introduces some relevant ideas and techniques from modern evolutionary theory, and from the mathematical and computational study of dynamical systems, and also offers a critique and review of some recent work on syntactic change in this emerging framework, arguing that a useful population model needs to support overlapping generations of language users and learners and to allow quite detailed modelling of differing demographic scenarios. I utilise simple linguistic scenarios based on constituent order changes to illustrate the ideas and techniques clearly. I abstract away from the sociolinguistic detail of the actuation

In this article the different features exhibited by four types of natural and artificial networks are reviewed, after a brief account of the basic quantitative characterizations that allow to measure network complexity. Some key questions that will be explored are: 1. What mechanisms have originated observed topological regularities in complex networks? 2. To what extent does optimization shape network topology ? 3. What is the origin of homeostasis in complex networks? 4. Is homeostasis a driving force or a side effect in network topology? 5. Is tinkering an inevitable component of network evolution ? 6. Are engineered systems free of tinkering? Comparison between the mechanisms that drive the building process of different graphs reveals that optimization might be a driving force, canalized in biological systems by both tinkering and the presence of conflicting constraints common to any hard multidimensional optimization process. Conversely, the presence of global features in technology graphs that closely resemble those observed in biological webs indicates that, in spite of the engineered design that should lead to hierarchical structures (such as the one shown in Figure 1) the tinkerer seems to be at work. 2. MEASURING NETWORK COMPLEXITY Since we are interested in comparing the global features of both biological and artificial (engineered) networks, we need to consider a number of quantitative measures in order to characterize them properly. In order to do so, the network structure is represented by a graph #, as before. Some of these measures (minimal distance, clustering coefficient) are usually applied to topological (i.e., static) descriptors of the graph structure, but others (entropy, redundancy, degeneracy) also apply to states that average dynamic variables

This paper investigates the formation of color categories and color naming in a population of agents. The agents perceive and categorize color stimuli, and try to communicate about these perceived stimuli. While doing so they adapt their internal representations to be more successful at conveying color meaning in future interactions. The agents have no access to global information or to the representations of other agents; they only exchange word forms. The factors driving the population coherence are the shared environment and the interactions. The experiments show how agents can form a coherent lexicon of color terms and --- particularly--- how a coherent color categorization emerges through these linguistic interactions. The results are interpreted in the light of theories describing and explaining universal tendencies in human color categorization and color naming. At the same time, the experiments confirm aspects of the theories of Luc Steels [1997; 1998] who vi...

This article reviews theories of organizational communication with a special emphasis on theories that have been used to explain computer-mediated communication phenomena. Among the theories reviewed, two—social presence and media richness—are identified as problematic and as posing obstacles to future theoretical development. While shortcomings of these theories have been identified in the past, some of these theories ’ predictions have been supported by empirical evidence. It is argued that this theoretical dilemma can be resolved based upon principles derived from a modern version of Darwin’s theory of evolution by natural selection and the application of those principles to the understanding of human evolution. A new theoretical model called the psychobiological model is developed, which predicts variations in cognitive effort in computer-mediated collaborative tasks. The model proposes that there is a negative causal link between the “naturalness ” of a computer-mediated communication medium, which is the similarity of the medium to the face-to-face medium, and the cognitive effort required from an individual using the medium for knowledge transfer. The model also states that this link is counterbalanced by what are referred to as “schema alignment ” and “cognitive adaptation. ” The schema alignment construct refers to the similarity between the mental schemas of an individual and those of other participant(s). The cognitive adaptation construct refers to an individual’s level of schema development associated with the use of a particular medium. Finally, the model states that the degree to which the medium supports an individual’s ability to convey and listen to speech is particularly significant in defining its naturalness, more so than the medium’s degree of