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

Cangelosi, Angelo (1999) Modeling the evolution of communication: From stimulus associations to grounded symbolic associations. [Conference Paper]

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Abstract

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.

Item Type:Conference Paper
Keywords:language evolution, neural networks, artificial life, syntax
Subjects:Computer Science > Artificial Intelligence
Computer Science > Neural Nets
Psychology > Evolutionary Psychology
Linguistics > Computational Linguistics
Psychology > Psychophysics
ID Code:2022
Deposited By: Cangelosi, Professor Angelo
Deposited On:11 Jan 2002
Last Modified:11 Mar 2011 08:54

References in Article

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