From Signaling to Word-Combination, a Layered Approach

We present a methodology by which multiword communication could one day be realized in a population of evolving Artificial Life agents. The method which combines genetic algorithms and artificial neural networks has the prospect of a gradual increase of communication complexity (multi-word communication) through a series of evolutionary phases that take place in tandem. This is a layered treatment of gradual increasing complexity thus making the framework suitable for computational investigations. We present an example in which agents evolve a shared lexicon that pertains to two concepts (direction and quantity) and address the issue of the ordering of the lexical forms of those concepts.