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The learning barrier: Moving from innate to learned systems of communication

Oliphant, Michael (1988) The learning barrier: Moving from innate to learned systems of communication. [Preprint] (Unpublished)

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Abstract

Human language is a unique ability. It sits apart from other systems of communication in two striking ways: it is syntactic, and it is learned. While most approaches to the evolution of language have focused on the evolution of syntax, this paper explores the computational issues that arise in shifting from a simple innate communication system to an equally simple one that is learned. Associative network learning within an observational learning paradigm is used to explore the computational difficulties involved in establishing and maintaining a simple learned communication system. Because Hebbian learning is found to be sufficient for this task, it is proposed that the basic computational demands of learning are unlikely to account for the rarity of even simple learned communication systems. Instead, it is the problem of *observing* that is likely to be central -- in particular the problem of determining what meaning a signal is intended to convey.

Item Type:Preprint
Keywords:language, communication, evolution, evolution of language, learning, language learnability, meaning, semantics, computation, hebbian learning, network learning, observational learning, associative learning, dynamical systems
Subjects:Biology > Animal Behavior
Biology > Animal Cognition
Biology > Evolution
Computer Science > Language
Computer Science > Dynamical Systems
Computer Science > Neural Nets
Linguistics > Computational Linguistics
Linguistics > Learnability
Linguistics > Semantics
Philosophy > Philosophy of Language
ID Code:196
Deposited By:Oliphant, Michael
Deposited On:15 Jun 1998
Last Modified:11 Mar 2011 08:53

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