Applying DNA Computation to Error Detection Problem in Rule-Based Systems

Abstract

As rule-based systems (RBS) technology gains wider acceptance, the need to create and maintain large knowledge bases will assume greater importance. Demonstrating a rule base to be free from error remains one of the obstacles to the adoption of this technology. In the past several years, a vast body of research has been carried out in developing various graphical techniques such as utilizing Petri Nets to analyze structural errors in rule-based systems, which utilize propositional logic. Four typical errors in rule-based systems are redundancy, circularity, incompleteness, and inconsistency. Recently, a DNA-based computing approach to detect these errors has been proposed. That paper presents algorithms which are able to detect structural errors just for special cases. For a rule base, which contains multiple starting nodes and goal nodes, structural errors are not removed correctly by utilizing the algorithms proposed in that paper and algorithms lack generality. In this study algorithms mainly based on Adleman's operations, which are able to detect structural errors, in any form that they may arise in rule base, are presented. The potential of applying our algorithm is auspicious giving the operational time complexity of O(n * (Max{q, K, z})), in which n is the number of fact clauses; q is the number of rules in the longest inference chain; K is the number of tubes containing antecedents which are comprised of distinct number of starting nodes; and z denotes the maximum number of distinct antecedents comprised of the same number of starting nodes.

Improvement of reliability of molecular DNA computing: solution of inverse problem of Raman spectroscopy using artificial neural networks

“…Further this approach was developed in a series of studies devoted to the solution of optimization problems: scheduling Laser Physics Improvement of reliability of molecular DNA computing: solution of inverse problem of Raman spectroscopy using artificial neural networks of work on elevators in multistory buildings [4,5] and laying cable in the trench (CTP-cable trench problem) [6]. With the help of DNA strands the random number generator was created [7], data encoding and decoding algorithms were made [8] and the search of structural errors in rule-based systems were elaborated upon [9]. With the help of DNA, Shu et al [10] solved the problem of calculating the optimal route.…”

Improvement of the fidelity of molecular DNA computations: control of DNA duplex melting using Raman spectroscopy

“…The suggested approach was developed further in the series of studies [10][11][12][13][14][15][16][17][18][19]. In [10] the possibility of using a DNA 'biocomputer' for the solution of the Boolean satisfiability problem was considered, and in [11] molecular computations were used for breaking one of the data encryption systems-DES (Data Encryption Standard System) with 256 different methods of data encryption.…”

“…In [18] the further development of the algorithm of data encryption and decryption based on DNA computations was suggested. In [19] molecular computations were used for searching for structural errors in the Rule-Based Systems. The suggested algorithm allowed them to find all the basic errors in Rule-Based Systems: Redundancy, Incompleteness, Circularity, and Inconsistency.…”