DNA Implementation of Fuzzy Inference Engine: Towards DNA Decision-Making Systems

Decision-making systems are an integral part of any autonomous device. With the recent developments in bio-nanorobots, smart drugs, and engineered viruses, there is an immediate need of decision-making systems which are bio-compatible in nature. DNA is considered a perfect candidate for designing the computing systems in such decision-making systems because of their bio-compatibility and programmability. Complex biological systems can be easily modeled/controlled using fuzzy logic operations with the help of linguistic rules. In this paper, we propose an enzyme-free DNA strand displacement-based architecture of fuzzy inference engine using the fuzzy operators, such as fuzzy intersection and union. The basic building blocks of this architecture are minimum, maximum, and fan-out gates. All these gates are analog in nature, which means that the input/output values of the gates are represented by the concentration of the input/output DNA strands. To demonstrate the performance of the proposed architecture, a detailed design, analysis, and kinetic simulation of each gate were carried out. Finally, the minimum and maximum gates are cascaded according to the pre-defined rules to design the fuzzy inference engine. All these DNA circuits are implemented and simulated in Visual DSD software.