Techniques for inferring a regular language, in the form of a finite automaton, from a sufficiently large sample of accepted and nonaccepted input words, have been employed to cons...
In this paper, we develop a symbolic representation for timed concurrent constraint (tccp) programs, which can be used for defining a lightweight model–checking algorithm for re...
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
—We introduce a new BDD-like data structure called Hybrid-Restriction Diagrams (HRDs) for the representation and manipulation of linear hybrid automata (LHA) state-spaces and pre...
High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...