Analyzing the Trade-Off Between Complexity Measures, Ambiguity in Insertion System and Its Applications

Insertion is one of the basic operations in DNA computing. Based on this operation, an evolutionary computation model, the insertion system, was defined. For the above defined evolutionary computation model, varying levels of ambiguity and basic descriptional complexity measures were defined. In this paper, we define twelve new (descriptional) complexity measures based on the integral parts of the derivation, such as axioms, strings to be inserted, and contexts used in the insertion rules. Later, we analyze the trade-off among the (newly defined) complexity measures and the existing ambiguity levels. Finally, we examine the application of the analyzed trade-off in natural languages and modelling of bio-molecular structures.

Automated summary

This paper explores the insertion operation in DNA computing and the evolutionary computation model based on it. By analyzing the trade-off between different complexity measures and levels of ambiguity, the application of these measures in natural language and bio-molecular structure modeling is examined.