EventsDIGITALISATION FOR A SUSTAINABLE SOCIETY
Event submissions
Published
with-doi10.3390/IS4SI-2017-04037
This submission belongs to the session Symposium 6. Theoretical Information Studies of the event DIGITALISATION FOR A SUSTAINABLE SOCIETY
Published date
09 Jun, 2017
Citation
Eugene Eberbach, Application of Information Theory Entropy as a Cost Measure in the Automatic Problem Solving, in Proceedings of DIGITALISATION FOR A SUSTAINABLE SOCIETY, Gothenburg, 12 June–16 June 2017, MDPI: Basel, Switzerland, doi: 10.3390/IS4SI-2017-04037
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Application of Information Theory Entropy as a Cost Measure in the Automatic Problem Solving

Eugene Eberbach 1
1. Dept. of Computer Science and Robotics Engineering Program, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609-2280, USA
Abstract

Abstract: We study the relation between Information Theory and Automatic Problem Solving to demonstrate that the Entropy measure can be used as a special case of $-Calculus Cost Functions measure.  We hypothesize that Kolmogorov Complexity (Algorithmic Entropy) can be useful to standardize $-Calculus Search (Algorithm) Cost Function.

Keywords
Manuscript
EbeSympBurginIS4SI17.pdf
Structures and Structural Information
Ecological Approach to Theoretical Information Studies