An Information-Theoretic Approach for the Quantification of Relevance

Polani, Daniel, Martinetz, Thomas and Kim, Jan (2008) An Information-Theoretic Approach for the Quantification of Relevance. In: Advances in Artificial Life. Lecture Notes in Computer Science, 2159 . Springer Berlin / Heidelberg, pp. 704-713.

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Abstract

We propose a concept for a Shannon-type quantification of information relevant to a decision unit or agent. The proposed measure is operational, can - at least in principle - be calculated for a given system and has an immediate interpretation as an information quantity. Its use as a natural framework for the study of sensor evolution is discussed.

Item Type:	Book Section
Additional Information:	6th European Conference, ECAL 2001 Prague, Czech Republic, September 10–14, 2001 Proceedings
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Computational Biology
Depositing User:	Vishal Gautam
Date Deposited:	03 Mar 2011 13:30
Last Modified:	21 Apr 2023 18:32
URI:	https://ueaeprints.uea.ac.uk/id/eprint/23080
DOI:	10.1007/3-540-44811-X_82

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