Affiliations: Department of Electrical and Computer Engineering,
University of Manitoba, 15 Gillson St., ENGR 504, Winnipeg, Manitoba R3T 5V6,
Canada | Institute of Mathematics, Warsaw University, Banacha 2,
02-097 Warsaw, Poland | Department of Foundations of Computer Science, University of Information Technology and Management, 35-225 Rzeszów, ul. H. Sucharskiego 2, Poland
Abstract: This paper considers models of sensors, filters, and sensor fusion
with Petri nets defined in the context of rough sets. Sensors and filters are
fundamental computational units in the design of systems. The intent of this
work is to construct Petri nets to simulate conditional computation in
approximate reasoning systems, which are dependent on filtered input from
selected sensors considered relevant in problem solving. In this paper,
coloured Petri nets provide a computational framework for the definition of a
family of Petri nets based on rough set theory. Sensors are modeled with what
are known as receptor processes in rough Petri nets. Filters are modeled as Łukasiewicz guards on some transitions in rough Petri nets. A Łukasiewicz
guard is defined in the context of multivalued logic. Łukasiewicz guards are
useful in culling from a collection of active sensors those sensors with the
greatest relevance in a problem-solving effort such as classification of a
"perceived" phenomenon in the environment of an agent. The relevance of a
sensor is computed using a discrete rough integral. The form of sensor fusion
considered in this paper consists in selecting only those sensors considered
relevant in solving a problem. The contribution of this paper is the modeling
of sensors, filters, and fusion in the context of receptor processes, Łukasiewicz guards, and rough integration, respectively.
