Possibilistic Assumption based Truth Maintenance System, Validation in a Data Fusion Application
This work addresses data fusion challenges for military decision-making, presenting an incremental improvement over existing methods.
The paper tackled the problem of data fusion in military applications by proposing a Possibilistic Assumption based Truth Maintenance System (n-ATMS), which resulted in improved situation synthesis from sensor data compared to a non-possibilistic solution.
Data fusion allows the elaboration and the evaluation of a situation synthesized from low level informations provided by different kinds of sensors. The fusion of the collected data will result in fewer and higher level informations more easily assessed by a human operator and that will assist him effectively in his decision process. In this paper we present the suitability and the advantages of using a Possibilistic Assumption based Truth Maintenance System (n-ATMS) in a data fusion military application. We first describe the problem, the needed knowledge representation formalisms and problem solving paradigms. Then we remind the reader of the basic concepts of ATMSs, Possibilistic Logic and 11-ATMSs. Finally we detail the solution to the given data fusion problem and conclude with the results and comparison with a non-possibilistic solution.