QUALITATIVE SUPPORT FOR KNOWLEDGE RETRIEVAL FOR AUTONOMOUS AGENTS

The problem of formal modeling of an information now in manufacturing agents (subsystems) consisting of people, machines, robots, and so on, matches very frequent real-life situations in which the following sho uld be answered: How to structure an exchange of information between t he elements of an agent? What is better, complete information but heav ily delayed, or incomplete information less delayed? The formal quanti tative model can be used to generate some examples of knowledge useful in answering these types of questions. Quantitative models of an info rmation now evaluation, however, are often too complex to serve as use ful tools in the knowledge retrieval process. In this paper, the appli cation of qualitative simulation in the process of knowledge acquisiti on for autonomous agents is investigated and illustrated with examples . The captured knowledge is codified as IF...AND...THEN production rul es and used in dependency networks supporting decisions concerning the structuring of information now.