抄録
A parallel reasoning process is studied, which is executed by intelligent sensors, each of whom is a member of a distributed sensor network (DSN). DSN is a new notable approach to situation assessment, that involves the acquiring and integrating of local information sensed from the world in order to produce a global interpretation. In this paper, each intelligent sensor has its own knowledge, a qualitative model about its concerning world and general law on the event evolution, both of which are utilized for predicting a future evolution after an observed event known by the local information obtained. Each of sensors generates a tree structure, qualitative evolutions after that event, by transitting states on that model to meet constraints, representations of general law. A tree structure, partial interpretations of a local information, involves branches caused by incompleteness of that information, lack about details. In order to integrate those interpretations into global ones, sensors exchange their own tree structures to prune branches which are inconsistent under global perspectives.
