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Simon Kirby
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Journal Articles
Publisher: Journals Gateway
Artificial Life (2006) 12 (2): 229–242.
Published: 01 April 2006
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We show how cultural selection for learnability during the process of linguistic evolution can be visualized using a simple iterated learning model. Computational models of linguistic evolution typically focus on the nature of, and conditions for, stable states. We take a novel approach and focus on understanding the process of linguistic evolution itself. What kind of evolutionary system is this process? Using visualization techniques, we explore the nature of replicators in linguistic evolution, and argue that replicators correspond to local regions of regularity in the mapping between meaning and signals. Based on this argument, we draw parallels between phenomena observed in the model and linguistic phenomena observed across languages. We then go on to identify issues of replication and selection as key points of divergence in the parallels between the processes of linguistic evolution and biological evolution.
Journal Articles
Publisher: Journals Gateway
Artificial Life (2003) 9 (4): 371–386.
Published: 01 October 2003
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Language is culturally transmitted. Iterated learning, the process by which the output of one individual's learning becomes the input to other individuals' learning, provides a framework for investigating the cultural evolution of linguistic structure. We present two models, based upon the iterated learning framework, which show that the poverty of the stimulus available to language learners leads to the emergence of linguistic structure. Compositionality is language's adaptation to stimulus poverty.
Journal Articles
Publisher: Journals Gateway
Artificial Life (2002) 8 (2): 185–215.
Published: 01 April 2002
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This article aims to show that linguistics, in particular the study of the lexico-syntactic aspects of language, provides fertile ground for artificial life modeling. A survey of the models that have been developed over the last decade and a half is presented to demonstrate that ALife techniques have a lot to offer an explanatory theory of language. It is argued that this is because much of the structure of language is determined by the interaction of three complex adaptive systems: learning, culture, and biological evolution. Computational simulation, informed by theoretical linguistics, is an appropriate response to the challenge of explaining real linguistic data in terms of the processes that underpin human language.
Journal Articles
Publisher: Journals Gateway
Artificial Life (2002) 8 (1): 87–100.
Published: 01 January 2002
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Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop's eight speakers, plus a section designed to reflect the debates that took place during the workshop's discussion sessions. The major theme that emerged during these sessions was the identity and status of artificial life as a scientific endeavor.