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Minimization of Automata

This chapter is concerned with the design and analysis of algorithms for minimizing finite automata. Getting a minimal automaton is a fundamental issue in the use and implementation of finite automata tools in frameworks like text processing, image analysis, linguistic computer science, and many other applications. There are two main families of minimization algorithms. The first by a sequence of refinements of a partition of the set of states, the second by a sequence of fusions or merges of states. Hopcroft's and Moore's algorithms belong to the first family, the linear-time minimization of acyclic automata of Revuz belongs to the second family. One of our studies is upon the comparison of the nature of Moore's and Hopcroft's algorithms. This gives some new insight in both algorithms. As we shall see, these algorithms are quite different both in behavior and in complexity. In particular, we show that it is not possible to simulate the computations of one of the algorithm by the other. We describe the minimization algorithm by fusion for so-called local automata. A special case of minimization is the construction o minimal automata for finite sets. We consider briefly this case, and in particular describe incremental algorithms. Finally, we consider the case of updating a minimal automaton when a word is added or removed from the set it recognizes.