A Model of the Distributed Constraint Satisfaction Problem and an Algorithm for Configuration Dising

IN THIS PAPER WE DISCUSS OUR APPROACH TO LEANING CLASSIFICATION RULES FROM DATA. WE SKETCH OUT TWO MODULES OF OUR ARCHITECTURE, NAMELY LINNEO AND GAR.LINNEO, WHICH IS A KNOWLWDGE ACQUISITION TOOL FOR ILL - STRUCTURED DOMAINS AUTOMATICALLY GENERATING CLASSES FROM EXAMPLES THAT INCREMENTALLY WORKS WHIT AN UNSUPERVISED STRATEGY. LINNEO'S OUTPUT, A REPRESENTATION OF THE CONCEPTUAL STRUCTURE OF THE DOMAIN IN TERMS OF CLASSES, IN THE INPUT TO GAR THAT IS USED TO GENERATE A SET OF CLASSIFICATION RULES FOR THE ORIGINAL TRAINING SET. GAR CAN GENERATE BOTH CONJUCTIVE AND DISJUNCTIVE RULES. HEREIN WE PRESENT AN APPLICATION OF THESE TECHNIQUES TO DATA OBTAINED FROM A REAL WASTEWATER TREATMENT PLANT IN ORDER TO HELP THE CONSTRUCTION OF A RULE BASE. THIS RULE WILL BE USED FOR A KNWOLEDGE - BASED SYSTEM THAT AIMS TO SUPERVISE THE WHOLE PROCESS.