INTELLIGENT ORGANIC COMPOUNDS AND FUELS DATABASE

MANY COMMERCIAL, GOVERNMENTAL, AND MILITARY ORGANIZATIONS TODAY MUST DEVELOP LARGE HIGHLY FLEXIBLE AND "INTELLIGENT" DATABASES IN SUCH A WAY THAT COMPLEX SYMBOLIC REASONING AND NUMERICAL COMPUTATION MUST BE CLOSELY INTEGRATED - FOR EXAMPLE, A DATABASE OF THERMODYNAMIC PROPERTIES OF ORGANIC FUELS SUPPORTING ANALYSIS AND SELECTION. THERE WILL BE LARGE VOLUMES OF NUMERIC AND TEXT DATA, WHICH MAY BE UNCERTAIN AND INCOMPLETE. NO EXISTING COMMERCIAL DBMS SYSTEMS CAN SUPPORT SUCH COMPLEXITY OR ADVANCED PROGRAMMING, AND NO AI LANGUAGES OR SHELLS PROVIDE SUFFICIENTLY ROBUST DATA MANAGEMENT TOOLS. MOREOVER, INTELLIGENT APPLICATIONS GENERALLY MUST BE ABLE TO ACCESS DATA PROVIDED BY OTHER APPLICATIONS STILL RUNNING ON THE TRADITIONAL DBMS CONTAINING THE ORIGINAL PRIMITIVE DATA. THE SOLUTION IS TO PROVIDE DIRECT INTERFACES BETWEEN AI PROGRAMMING LANGUAGES AND RELATIONAL DBMSS, AS HAS BEEN DONE BY APPLIED LOGIC SYSTEMS, INC., WITH ITS PROLOG-DBMS INTERFACES. THE SITUATION CREATES A DEMAND AND AN OPPORTUNITY TO EXTEND THESE POWERFUL TOOLS TO CONSTRUCT TRULY INTELLIGENT DATABASES, SUCH AS THE REQUESTED FUELS DATABASE. THE PRESENT PROPOSAL ADDRESSES THE APPLICATION AND EXTENSION OF THE PRESENT TOOLS TO THE CONSTRUCTION OF AN INTELLIGENT FUELS DATABASE, AND THE ABSTRACTION/EXTRACTION OF THE GENERAL TOOLS FOR APPLICATION TO SIMILAR SETTINGS.