Search

We describe how current work in Artificial Intelligence is using rigorous tools from information theory, namely information distance and experience distance to organize the self-structuring of sensorimotor perception, motor control, and experiential episodes with extended temporal horizon. Experience is operationalized from an embodied agent's own perspective as the flow of values taken by its sensors and effectors (and possibly other internal variables) over a temporal window. Such methods allow an embodied agent to acquire the sensorimotor fields and control structure of its own body, and are being applied to pursue autonomous scaffolded proximal development in the zone between the familiar experience and the unknown. [ABSTRACT FROM AUTHOR]

In this chapter we present evidence that there is an underlying local sequential structure in present day language, and suggest that the components of such a structure could have been the basis of a more highly evolved hierarchical grammar. The primary local sequential structure is shown to have its own benefits, which indicate that there could be an intermediate stage in the evolution of grammar, before the advantages of a fully developed syntax were realised. [ABSTRACT FROM AUTHOR]

This book brings together work on the emergence of communication and language from researchers working in a broad array of scientific paradigms in North America, Europe, Japan and Africa. [ABSTRACT FROM AUTHOR]

Neuroscientists have suggested that the mirror-neurons in our primate ancestors may have provided a substrate for the emergence of language in humans. Simulation studies of the emergence of language, using minimal implementations of proposed mechanisms, are a way to assess their explanatory power for the emergence and evolution of communication. In this work, we study the emergence and stability of linguistic labelling in a communities of agents with mirror-neuron mechanisms for associating deictic reference with speech utterances. These minimal agents possessing a built-in mirror-neuron style temporal recurrent neural network architecture are capable of perceiving and carrying out deixis (‘pointing') to refer to others in their group, as well as producing and perceiving utterances of another agent in their group. They are able to generate and learn temporally extended phonetic utterances (‘names') and associate these to deictic referents. Thus, the agents utter what they hear, and tend refer to the same entities as another agent that they watch when it points. Previous work has shown the emergence and stability of arbitrary names generated by the agents in certain fixed topologies of interaction. In this work, we systematically study the effects of different interaction topologies on the dynamics of convergence to a common vocabulary in the population, and its stability over time. Results show that certain topologies of interaction to be more conducive than others to the emergence of a stable vocabulary. Moreover, some topologies of interaction (such as cycles) are seen to yield instability and to amplify feedback given the mirror-neuron system. Linguistic convergence and change bear similarity to those of natural language. Homophony and multiple referents of particular proto-words may also emerge. In light of results, we suggest that mechanisms for confirming joint-attention and for suppression of mirroring could play an essential role in maintaining stability in the emergence of linguistic reference. [ABSTRACT FROM AUTHOR]

Human language may have evolved through a stage when words were combined into structured linear segments, before these segments were used as building blocks for a hierarchical grammar. This hypothesis is approached by examining the apparently ubiquitous prevalence of homophones. It suggests how, perhaps contrary to expectation, communicative capacity does not seem to be adversely affected by homophones, and how it is that they can be routinely used without confusion. These facts are principally explained by disambiguation through syntactic processing of short word sequences. Local sequential processing plays an underlying role in language production and perception, a hypothesis that is supported by evidence that small children engage in this process as soon as they acquire words. Experiments on a corpus of spoken English calculated the entropy for sequences of syntactically labelled words. They show there is a measurable advantage in decoding word strings when they are taken in short sequences, rather than as individual items. This suggests that grammatical fragments of speech could have been a stepping stone to a full grammar. [ABSTRACT FROM AUTHOR]