An Information-Theoretic Approach for the Quantification of Relevance

Daniel Polani, Thomas Martinetz, Jan K. Kim

Research output: Chapter in Book/Report/Conference proceedingChapter

19 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationAdvances in Artificial Life
EditorsJozef Kelemen, Petr Sosík
PublisherSpringer Berlin / Heidelberg
Pages704-713
Number of pages10
Volume2159
DOIs
Publication statusPublished - 2008

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin / Heidelberg

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