ACM Computing Surveys (CSUR)
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We present a theory about the logical relationships associated with system behavior. The rules governing the behavior of a system are expressed by a Petri net. A set of assumptions about the modeling of a system permit us to separate system behavior into two components, what we refer to as information and control. Information is concerned with choices and how they are resolved. Control is concerned with the fixed, repetitive aspects of behavior - those aspects that are independent of choices. We develop a concept of information that is nonprobabilistic. It is not inconsistent with Shannon''s approach, but simply proceeds from a more basic idea: It deals with possibilities, rather than probabilities. Our approach embodies four common notions about information: (1) information distinguishes between alternatives; (2) it resolves choices; (3) it is transmitted and transformed within a system; (4) it says something about past behavior (memory or postcondition) and something about future behavior (prediction). We can identify those points at which information either enters or leaves a system, and we can trace information as it flows through a system. The control component of system behavior is determined by a system''s control structure, which is an event graph (marked graph). We show how the control structure of a system may be interpreted as the system''s space/time framework. When considered separately, theories of information and control are of limited applicability. When brought together, they provide a technique for predicting and postdicting behavior.