Exact and heuristic algorithms for the minimization of incompletely specified state machines

Abstract

Presents two exact algorithms for state minimization of FSM's. The authors' results prove that exact state minimization is feasible for a large class of practical examples, certainly including most hand-designed FSM's. They also present heuristic algorithms, that can handle large, machine-generated, FSM's. They argue that the true objective of state reduction should be reduction toward maximal encodability. The state mapping problem has received almost no prior attention in the literature. They show that mapping plays a significant role in delivering an optimally implemented reduced machine. They also introduce an algorithm whose main virtue is the ability to cope with very general cost functions, while providing very high performance.