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A Theory of Semantic Information in the Context of its Ecology
University of Posts & Telecommunications, Beijing, China.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-9881-400X
2020 (English)In: Theoretical Information Studies: Information in the World / [ed] Mark Burgin and Gordana Dodig-Crnkovic, Singapore: World Scientific, 2020, p. 81-112Chapter in book (Other academic)
Abstract [en]

In the theory of human communication, information is described as the trinity of aspects, or dimensions: syntactic, semantic, and pragmatic, corresponding, respectively, to the formthe meaning, and the utility of information. The theory of information proposed by Shannon in 1948, often considered as “the” theory of information, is a purely statistical theory of communication of syntactic information. Both the semantic and pragmatic theories of information, which are in the first place significant for human understanding, are still lacking. In this chapter, an ecological theory of semantic information is presented in the context of human communication and in the case of symbolic artificial intelligence. The novelty of the approach is that information is studied in the context of its ecology and not reduced to only one of its aspects. It is shown that the semantic information can be used as the unique representative for the trinity of information aspects. The same ecological approach can be applied in the case of embodied intelligence without representation, where the world is considered the best model of itself, which remains for future research. The same goes for the generalization to the system of communicating cognizing/ intelligent agents. Another domain of high interest for further exploration is the temporal aspect of ecological information, including its evolution. Related to this, the development in the direction of a new, more appropriate logical basis is necessary.

Place, publisher, year, edition, pages
Singapore: World Scientific, 2020. p. 81-112
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-50001DOI: 10.1142/9789813277496_0006ISBN: 9813277483 (print)OAI: oai:DiVA.org:mdh-50001DiVA, id: diva2:1466123
Available from: 2020-09-10 Created: 2020-09-10 Last updated: 2020-09-10Bibliographically approved

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