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 & Rumbaughs (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 Deacons (1997) hypothesis on the role of symbolic acquisition for the origin of language are discussed.
Item Type: | Conference Paper |
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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 |
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