Title :
Efficient search techniques for the inference of minimum size finite automata
Author :
Oliveira, Arlindo L. ; Silva, Joao P M
Author_Institution :
Cadence Eur. Labs., IST-INESC, Lisbon, Portugal
Abstract :
We propose a new algorithm for the inference of the minimum size deterministic automaton consistent with a prespecified set of input/output strings. Our approach improves a well known search algorithm proposed by A.W. Bierman and J.A. Feldman (1972), by incorporating a set of techniques known as dependency directed backtracking. These techniques have already been used in other applications, but we are the first to apply them to this problem. The results show that the application of these techniques yields an algorithm that is, for the problems studied, orders of magnitude faster than existing approaches
Keywords :
backtracking; deterministic automata; finite automata; inference mechanisms; search problems; string matching; dependency directed backtracking; input/output strings; minimum size deterministic automaton; minimum size finite automata inference; search algorithm; search techniques; Circuit synthesis; Doped fiber amplifiers; Gold; Inference algorithms; Laboratories; Learning automata; Logic circuits; Logic design; Machine learning; Polynomials;
Conference_Titel :
String Processing and Information Retrieval: A South American Symposium, 1998. Proceedings
Conference_Location :
Santa Cruz de La Sierra
Print_ISBN :
0-8186-8664-2
DOI :
10.1109/SPIRE.1998.712986