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ICGI
2010
Springer

Inferring Regular Trace Languages from Positive and Negative Samples

13 years 3 months ago
Inferring Regular Trace Languages from Positive and Negative Samples
In this work, we give an algorithm that infers Regular Trace Languages. Trace languages can be seen as regular languages that are closed under a partial commutation relation called the independence relation. This algorithm is similar to the RPNI algorithm, but it is based on Asynchronous Cellular Automata. For this purpose, we define Asynchronous Cellular Moore Machines and implement the merge operation as the calculation of an equivalence relation. After presenting the algorithm we provide a proof of its convergence (which is more complicated than the proof of convergence of the RPNI because there are no Minimal Automata for Asynchronous Automata), and we discuss the complexity of the algorithm.
Antonio Cano Gómez
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2010
Where ICGI
Authors Antonio Cano Gómez
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