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Content in Simple Signalling Systems

Content in Simple Signalling Systems Our understanding of communication and its evolution has advanced significantly through the study of simple models involving interacting senders and receivers of signals. Many theorists have thought that the resources of mathematical information theory are all that are needed to capture the meaning or content that is being communicated in these systems. However, the way theorists routinely talk about the models implicitly draws on a conception of content that is richer than bare informational content, especially in contexts where false content is important. This article shows that this concept can be made precise by defining a notion of functional content that captures the degree to which different states of the world are involved in stabilizing senders’ and receivers’ use of a signal at equilibrium. A series of case studies is used to contrast functional content with informational content, and to illustrate the explanatory role and limitations of this definition of functional content.1 Introduction2 Modelling Framework3 Two Kinds of Content  3.1 Informational content  3.2 Functional content4 Cases  4.1 Case 1: Simplest case  4.2 Case 2: Partial pooling  4.3 Case 3: Bottleneck  4.4 Case 4: Partial common interest  4.5 Case 5: Deception  4.6 Case 6: A further problem arising from divergent interests5 DiscussionAppendix  http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The British Journal for the Philosophy of Science Oxford University Press

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Publisher
Oxford University Press
Copyright
© The Author 2017. Published by Oxford University Press on behalf of British Society for the Philosophy of Science.
ISSN
0007-0882
eISSN
1464-3537
DOI
10.1093/bjps/axw036
Publisher site
See Article on Publisher Site

Abstract

Our understanding of communication and its evolution has advanced significantly through the study of simple models involving interacting senders and receivers of signals. Many theorists have thought that the resources of mathematical information theory are all that are needed to capture the meaning or content that is being communicated in these systems. However, the way theorists routinely talk about the models implicitly draws on a conception of content that is richer than bare informational content, especially in contexts where false content is important. This article shows that this concept can be made precise by defining a notion of functional content that captures the degree to which different states of the world are involved in stabilizing senders’ and receivers’ use of a signal at equilibrium. A series of case studies is used to contrast functional content with informational content, and to illustrate the explanatory role and limitations of this definition of functional content.1 Introduction2 Modelling Framework3 Two Kinds of Content  3.1 Informational content  3.2 Functional content4 Cases  4.1 Case 1: Simplest case  4.2 Case 2: Partial pooling  4.3 Case 3: Bottleneck  4.4 Case 4: Partial common interest  4.5 Case 5: Deception  4.6 Case 6: A further problem arising from divergent interests5 DiscussionAppendix 

Journal

The British Journal for the Philosophy of ScienceOxford University Press

Published: Dec 1, 2018

References