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A Rough Set Approach to Real-Time State Indentification for Decision Making.

Skowron, A.; Suraj, Z.

In: 93, Warsaw University of Technology: Institute of Computer Science Research Report 18. 1993.

Abstract: We consider decision tables assuming that the values (local states) of conditions are measured by sensors. These sensors produce outputs after unknown (but finite) number of time units. We construct an algorithm for computing from a given decision table a highly parallel program (represented by Petri net). Our approach is based on the rough set theory. The constructed net allows to identify global states (objects in decision tables) to the extent which make possible to take an appropriate decision. The outputs from sensors are propagated through the net with the maximal speed. This is done by an appropriate implementation of all decision rules true in a given decision table. Our approach seems to have some value for theoretical foundations of real-time systems.


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