AN ELECTRONIC SYSTEM TROUBLESHOOTING PROGRAM USING ARTIFICIAL INTELLIGENCE TECHNIQUES.

WE PROPOSE TO STUDY AND CONSTRUCT AN ARTIFICAL INTELLIGENCE PROGRAM WHICH CAN IDENTIFY ELECTRONIC MALFUNCTIONS, THEN LEARN FROM ITS SUCCESSES AND FAILURES TO BE MORE EFFICIENT, ACCURATE, AND EXPERT. THE PROGRAN WILL DRAW ON A DATABASE OF GENERAL TROUBLESHOOTING TECHNIQUES, SPECIFIC DEVICE KNOWLEDEG, AND EXPERIENCE WITH THE SYSTEM UNDER TEST TO DIRECT A TECHNICIAN'S DEBUGGING ACTIVITIES. THE PROGRAM WILL ASK THE TECHNICIAN FOCUSED QUESTIONS ABOUT THE SYSTEM'STHE QUESTIONS WILL REGUIRE PROBING FOR VOLTEGES, LOGIC LEVELS, ETC. THE INFORMATION GENERATED WILL LED TO MORE QUESTIONS, UTILIMATELY RESULTING IN RECOMMENDATIONS FOR REPAIR. CORRECT ANALYTIC CONCLUSIONS WILL BE INCORPORATED INTO THE PROGRAM'S MEMORY, REDUCING THE TIME TO FIND THE SAME PROBLEM THEREAFTER. TECHNICIANS WILL BE ABLE TO QUESTION WRONG CONCLUSIONS AND TO UNCOVER THE LOGIC LEADING TO THE ERRORS. MALFUNCTIONS LOCATED BY PROGRAM RECOMMENDATIONS OR BY TECHINICIANS HENCE INCREASE THE PROGRAM'S KNOWLEDGE. MISTAKES ALSO LEAD TO NEW KNOWLEDGE AND THE FORMULATION OF NEW PROGRAM RULES WITHIN THE KNOWLEDGE BASE. THE PROGRAM AMPLIFIES AND EXTENDS THE TECHINICIAN'S EXPERTISE. OVERALL, THE PROJECT WILL MODEL AND ELABORATE AI PROGRAMS NOW RUNNING SUCCESSFULLY IN OTHER FIELDS, AND WILL UTILIZE ADA FOR MAXIMUM SYSTEMIC UTILITY.