Little research has been conducted so far on causes for errors in business process models. In this paper we investigate on how mainly domain independent factors such as the size or...
We present a trainable sequential-inference technique for processes with large state and observation spaces and relational structure. Our method assumes "reliable observation...
Over the last years, particle filters have been applied with great success to a variety of state estimation problems. We present a statistical approach to increasing the efficienc...
Abstract. In this paper we tackle the problem of coordinating multiple decentralised agents with continuous state variables. Specifically we propose a hybrid approach, which combin...
Thomas Voice, Ruben Stranders, Alex Rogers, Nichol...
Symbolic model checking has proved highly successful for large nite-state systems, in which states can be compactly encoded using binary decision diagrams (BDDs) or their variants...