CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
The Role of Anticipation in the Emergence of Language
Anticipatory Behavior in Adaptive Learning Systems
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This paper describes a model for the evolution of communication systems using simple syntactic rules, such as word combinations. It also focuses on the distinction between simple word-object associations and symbolic relationships. The simulation method combines the use of neural networks and genetic algorithms. The behavioral task is influenced by Savage-Rumbaugh & Rumbaugh's (1978) ape language experiments. The results show that languages that use combination of words (e.g. "verb-object" rule) can emerge by autoorganization and cultural transmission. Neural networks are tested to see if evolved languages are based on symbol acquisition. The implications of this model for Deacon's (1997) hypothesis on the role of symbolic acquisition for the origin of language are discussed.