Language Evolution and Computation Bibliography

We show how a population of simulated robots developed their communication capabilities in order to solve a collective navigation problem. The self-organized emergent vocabulary includes four different signals that influence both the motor and signalling behaviour of other robots. The analysis of the evolved behaviours also indicates: (a) the emergence of a simple form of communication protocol that allows individuals to switch signalling on and off, (b) the emergence of tightly co-adapted communicative and non-communicative behaviours, and (c) the exploitation of properties resulting from the dynamical interactions between motor and signalling behaviours produced by interacting robots.

The paper describes a neural network model of early language acquisition with an emphasis on how language positively influences the categories with which the child categorizes reality. Language begins when the two separate networks that are responsible for nonlinguistic sensory-motor mappings and for recognizing and repeating linguistic sounds become connected together at 1 year of age. Language makes more similar the internal representations of different inputs that must be responded to with the same action and more different the internal representations of inputs that must be responded to with different actions.