Most symbolic model checkers are based on either Binary Decision Diagrams (BDDs), which may grow exponentially large, or Satisfiability (SAT) solvers, whose time requirements rapi...
Participatory methods can, in principle, be applied for a variety of purposes to gain insight into the context of use of an artefact or the way in which tasks are performed by end ...
We present a methodology for the modeling of complex program behavior in CLP. In the first part we present an informal description about how to represent a system in CLP. At its ...
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
We present a symbolic algorithm for strongly connected component decomposition. The algorithm performs (n log n) image and preimage computations in the worst case, where n is the n...