Abstract
The problem of formal modeling of an information flow in manufacturing agents subsystems consisting of people, machines, robots, and so on, matches very frequent real-life situations in which the following should be answered: How to structure an exchange of information between the elements of an agent? What is better, complete information but heavily delayed, or incomplete information less delayed? The formal quantitative model can be used to generate some examples of knowledge useful in answering these types of questions. Quantitative models of an information flow evaluation, however, are often too complex to serve as useful tools in the knowledge retrieval process. In this paper, the application of qualitative simulation in the process of knowledge acquisition for autonomous agents is investigated and illustrated with examples. The captured knowledge is codified as IF...AND...THEN production rules and used in dependency networks supporting decisions concerning the structuring of information flow.
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