Using Knowledge in a Logistical Multi-Agent Scenario

W. Dangelmaier, P. Scheideler, and A. Döring (Germany)


Knowledge Based Systems, Intelligent Transportation Systems


In this paper, a scheme is outlined within which autonomous agents (shuttles) in an intelligent transportation system exchange knowledge about their environment. Benefiting from each other’s knowledge, the shuttles can locally adapt their behaviour in order to perform the desired flexible adjustments of the overall system behaviour. Based on the shuttles’ shared knowledge, an exploration and planning strategy for selecting routes according to a set of given customer constraints is described. Meanwhile, sensor input from the environment is used to cooperatively learn the best routes and keep the knowledge about the world up-to date.

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