On Some Properties of Maximal Prefix Codes and Machine Learning for Automata
Nikolai I. Krainiukov, Mikhail Abramyan, Boris Feliksovich Melnikov · Frontiers in artificial intelligence and applications · 2024
In this paper we study the prefix codes and application of prefix codes for problem of machine learning for deterministic finite state automaton. We give an example for the problem of constructing an inverse morphism, also parameterized by the number of transitions of automata. We investigate the factorization of prefix codes can give more simple structure of DFA for understanding his behaviors. To verify the correctness of the proposed approach, we implemented a system computer algebra GAP that accurately performs the logical flow of algorithm cycle by cycle.