Uncertain temporal reasoning for the distributed transportation scheduling problem

Distributed artificial intelligence (DAI) is suitable to applications where there is no central control. One of these applications with which we are concerned is transportation scheduling. We have noticed that all the approaches dedicated to this application use a weak representation of time and simple reasoning. Furthermore, these approaches ignore the uncertain behavior of agents. We propose an approach based on fuzzy temporal characteristic functions (FTCF) which allow a powerful representation of agent company behaviors, continually informing us about the degree of agent availability. Using this representation, we develop a temporal reasoning which allows inter and intra company cooperation to allocate trucks and to delegate orders.