exact and heuristic algorithms for the minimization of incompletely specified state machines
In this paper we present two exact algorithms for state minimization of FSM's. Our results prove that exact state minimization is feasible for a large class of practical examples, certainly including most hand-designed FSM's. We also present heuristic algorithms, that can handle large, machine-generated, FSM's. We 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. We show that mapping plays a significant role in delivering an optimally implemented reduced machine. We also introduce an algorithm whose main virtue is the ability to cope with very general cost functions, while providing very high performance.
heuristic algorithm algorithm minimal state machine paper class practical examples general object reduction map attention role cost high-performance