Learning Limited Context Restarting Automata by Genetic Algorithms

Abstrakt

We propose a genetic algorithm for learning restricted vari- ants of restarting automata from positive and negative samples. Exper- iments comparing the proposed genetic algorithm to algorithms RPNI and LARS on sample languages indicate that the new algorithm is able to infer a target language even from a small set of samples.

Klíčová slova

• grammatical inference
• limited context restarting automata
• formal languages
• genetic algorithms