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

Authors:
Wilhelm Dangelmaier;Benjamin Klopper;Jens Wienstroer;Thorsten Timm
Affiliations:
University of Paderborn, Germany;University of Paderborn, Germany;University of Paderborn, Germany;University of Paderborn, Germany
Venue:
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
Year:
2006

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Cited 1

An Agent Based Modelling Approach for Stochastic Planning Parameters

HoloMAS '07 Proceedings of the 3rd international conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing

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Abstract

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.