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Proceedings 2017, 1(3), 94; doi:10.3390/IS4SI-2017-03942

Meaning Generation for Animals, Humans and Artificial Agents. An Evolutionary Perspective on the Philosophy of Information

Independant scholar, Bordeaux, France
Presented at the IS4SI 2017 Summit DIGITALISATION FOR A SUSTAINABLE SOCIETY, Gothenburg, Sweden, 12–16 June 2017.
Published: 8 June 2017
Download PDF [260 KB, uploaded 2 August 2017]

Abstract

Meanings are present everywhere in our environment and within ourselves. But these meanings do not exist by themselves. They are associated to information and have to be created, to be generated by agents. The Meaning Generator System (MGS) has been developed to model meaning generation in agents following a system approach in an evolutionary perspective. The agents can be natural or artificial. The MGS generates meaningful information (a meaning) when it receives information that has a connection with an internal constraint to which the agent is submitted. The generated meaning is to be used by the agent to implement actions aimed at satisfying the constraint. We propose here to highlight some characteristics of the MGS that could be related to items of philosophy of information.
Keywords: information; meaning; constraint; representation; evolution; self-consciousness; anxiety management; philosophy of information; ethics; symbol grounding problem information; meaning; constraint; representation; evolution; self-consciousness; anxiety management; philosophy of information; ethics; symbol grounding problem
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Menant, C. Meaning Generation for Animals, Humans and Artificial Agents. An Evolutionary Perspective on the Philosophy of Information. Proceedings 2017, 1, 94.

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