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Complexity, Emergence and Molecular Diversity via Information Theory
Abstract
Numerous definitions for complexity have been proposed with little consensus. The definition here is related to Kolmogorov complexity and Shannon entropy measures. However, the price is to introduce context dependence into the definition of complexity. Such context dependence is an inherent property of complexity. Scientists are uncomfortable with such context dependence that smacks of subjectivity, which is the reason why little agreement is found on the meaning of the terms. In an article published in Molecules, Lin presented a novel approach for assessing molecular diversity based on Shannon information theory. A set of compounds is viewed as a static collection of microstates that can register information about their environment. The method is characterized by a strong tendency to oversample remote areas of the feature space and produce unbalanced designs. This chapter demonstrates the limitation with some simple examples and provides a rationale for the failure to produce results that are consistent.
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