The Shortest Path Problem in Uncertain Domains -- an Agent based Approach with Bayesian Networks

Real world problems, e.g. from transport domain, are typically non-deterministic and uncertain. Although many approaches, especially form the area of operations research assume constant parameters like ride duration or availability of connections in networks, these parameters depend on a large number of influences and are not constant. The paradigm of Bayesian thinking teaches us, that we can use partial knowledge of the influences to derive better estimations of these variables. In this paper, we introduce a multiagent system (MAS) that implements a distributed hybrid Bayesian network and is able to create a dynamic probabilistic model of the shortest path problem, in order to create better estimation and thereby better plans