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.
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Application of Information Theory Entropy as a Cost Measure in the Automatic Problem Solving
Published: 09 June 2017 by MDPI in DIGITALISATION FOR A SUSTAINABLE SOCIETY session Theoretical Information Studies