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Modeling the evolution of communication: From stimulus associations to grounded symbolic associations

By Angelo Cangelosi


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 auto-organization 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

Topics: Artificial Intelligence, Neural Nets, Evolutionary Psychology, Computational Linguistics, Psychophysics
Publisher: Speinger Verlag
Year: 1999
DOI identifier: 10.1007/3-540-48304-7_86
OAI identifier:

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