Hereditarily finite (HF) set theory provides a standard universe of sets, but with no infinite sets. Its utility is demonstrated through a formalisation of the theory of regular languages and finite automata, including the Myhill-Nerode theorem and Brzozowski's minimisation algorithm. The states of an automaton are HF sets, possibly constructed by product, sum, powerset and similar operations.
Recent Isabelle developments explicitly bypass automata theory. @cite_2 prove the Myhill-Nerode theorem using regular expressions. This is a significant feat, especially considering that the theorem's underlying intuitions come from automata. Current work on regular expression equivalence @cite_10 @cite_0 continues to focus on regular expressions rather than finite automata.
@cite_0 @cite_10 @cite_2
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There are numerous textbooks on regular languages. Many of them focus on finite automata for proving properties. Unfortunately, automata are not so straightforward to formalise in theorem provers. The reason is that natural representations for automata are graphs, matrices or functions, none of which are inductive datatypes. Regular expressions can be defined straightforwardly as a datatype and a corresponding reasoning infrastructure comes for free in theorem provers. We show in this paper that a central result from formal language theory--the Myhill-Nerode Theorem--can be recreated using only regular expressions. From this theorem many closure properties of regular languages follow. A generalization from string to trees and from languages to translations is given of the classical result that any regular language can be learned from examples: it is shown that for any deterministic top-down tree transformation there exists a sample set of polynomial size (with respect to the minimal transducer) which allows to infer the translation. Until now, only for string transducers and for simple relabeling tree transducers, similar results had been known. Learning of deterministic top-down tree transducers (dtops) is far more involved because a dtop can copy, delete, and permute its input subtrees. Thus, complex dependencies of labeled input to output paths need to be maintained by the algorithm. First, a Myhill-Nerode theorem is presented for dtops, which is interesting on its own. This theorem is then used to construct a learning algorithm for dtops. Finally, it is shown how our result can be applied to xml transformations (e.g. xslt programs). For this, a new dtd-based encoding of unranked trees by ranked ones is presented. Over such encodings, dtops can realize many practically interesting xml transformations which cannot be realized on firstchild next-sibling encodings. We introduce the notion of topological entropy of a formal language as the topological entropy of the minimal topological automaton accepting it. Using a characterization of this notion in terms of approximations of the Myhill–Nerode congruence relation, we are able to compute the topological entropies of certain example languages. Those examples suggest that the notion of a “simple” formal language coincides with the language having zero entropy. The Nerode realization technique for synthesizing finite-state machines from their associated right-invariant equivalence relations is modified to give a method for synthesizing machines from finite subsets of their input?output behavior. The synthesis procedure includes a parameter that one may adjust to obtain machines that represent the desired behavior with varying degrees of accuracy and that consequently have varying complexities. We discuss some of the uses of the method, including an application to a sequential learning problem.