An artificial life approach to language.
The aim of the paper is to show that an Artificial Life approach to language tends to change the research agenda on language which has been shared by both the symbolic paradigm and classical connectionism. Artificial Life Neural Networks (ALNNs) are different from classical connectionist networks because they interact with an independent physical environment; are subject to evolutionary, developmental, and cultural change, and not only to learning; and are part of organisms that have a physical body, have a life (are born, develop, and die), and are members of genetic and sometimes, cultural populations. Using ALNNs to study language shifts the emphasis from research on linguistic forms and laboratory-like tasks to the investigation of the emergence and transmission of language, the use of language, its role in cognition, and language as a populational rather than as an individual phenomenon.
Parisi
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Institute of Psychology, National Research Council, Rome, Italy. domenico@kant.irmkant.rm.cnr.it
D000819:Animal Communication; D000818:Animals; D003469:Culture; D006801:Humans; D007802:Language; D016571:Neural Networks, Computer