Finite State Machine Synthesis for Evolutionary Hardware

TL;DR

This paper presents a genetic algorithm-based method for synthesizing finite state machines that reduces state count and synthesis time, enabling efficient implementation on reconfigurable hardware for autonomous systems.

Contribution

It introduces a novel genetic algorithm approach for finite state machine synthesis that improves efficiency and reduces complexity compared to traditional methods.

Findings

Reduced number of states in synthesized machines

Faster synthesis process

Potential for deployment in autonomous reconfigurable systems

Abstract

This article considers application of genetic algorithms for finite machine synthesis. The resulting genetic finite state machines synthesis algorithm allows for creation of machines with less number of states and within shorter time. This makes it possible to use hardware-oriented genetic finite machines synthesis algorithm in autonomous systems on reconfigurable platforms.