Efficient indexing schemes have influenced the acceptance of production systems in the industrial world. However, in embedded-control systems, production systems have not been applied intensively because of their nondeterministic run-time behavior. Thus, nonpredictability of response times is a major obstacle to the widespread use of expert systems in the real-time domain. Such systems are considered intelligent when they are able to perform complex actions in response to the sensed environment. In intelligent real-time systems, there is a tradeoff between acting and reasoning.

Artificial Intelligence is solving more and more real world problems, but penetration into the complexities of government administration has been minimal. The author suggests that combining expert system technology with conventional procedural computer systems can lead to substantial efficiencies. Business rules can be removed from business-oriented computer systems and stored in a separate but integrated knowledge base, where maintenance will be centralized. Fourteen specific practical applications are suggested. Traditionally, these systems have been used to automate the accounting function, automate labor-intensive activities, manage and control vast financial and physical assets, process payrolls for hundreds of thousands of employees, and merge and summarize information about a wide set of activities in support of management decision making.

Southwest Research Institute and the U.S. Air Force Materiel Command designed and developed an automated system for the preparation of deficiency report analysis information reports ( Engineers and equipment specialists responsible for the troublesome part, or end item, review the MDR to identify the possible cause(s) of failure. In the past, engineers and equipment specialists have turned to operations research (OR) analysts to assist in item performance analysis. This analysis is usually time consuming and personnel intensive and requires information from many Air Force data systems. At the Oklahoma City Air Logistics Center (ALC), located at Tinker Air Force Base, data collection and analysis require two person-days. This document describes an item's SOURCE DATA: The data used to prepare this report came from the following sources: 1) Product Performance Subsystem (G099), 2) Supportability analysis Forecasting Evaluation (SAFE), 3) Flying Hours (G099), 4) MICAP Hours (D165B), and 5) VAMOSC (D160B).

Custom DU is an automated underwriting system that enables mortgage lenders to build their own business rules that facilitate assessing borrower eligibility for different mortgage products. Developed by Fannie Mae, Custom DU has been used since 2004 by several lenders to automate the underwriting of numerous mortgage products. Custom DU uses rule specification language techniques and a web-based, user-friendly interface for implementing business rules that represent business policy. By means of the user interface, lenders can also customize their underwriting findings reports, test the rules that they have defined, and publish changes to business rules on a real-time basis, all without any software modifications. The user interface enforces structure and consistency, enabling business users to focus on their underwriting guidelines when converting their business policy to rules.

Loan underwriting is the process of evaluating a loan application to determine whether the loan should be funded. The process often starts with a potential borrower walking into a branch office and requesting a loan to purchase or refinance a home. A processor asks the borrower to fill out an application, setting in motion a lengthy information-gathering process in which as many as 1500 data-element pieces will eventually be collected. This loan information includes items about the borrower's employment, income, assets, liabilities, and monthly expenses. During the process, a credit report and appraisal will be ordered from a third-party vendor.

Introduction The development of advanced robotics brought expectations of increased productivity and quality control, but to everyone's disappointment, these expectations still have not been realized. Advanced stand-alone machines have not greatly improved productivity, and integrating large systems has been prohibitively expensive. What is worse, the few integration projects that have been undertaken took inordinate amounts of engineering time. Several projects took more than 50 man-years to complete, and engineers spent most of this time trying to put round plugs into square sockets. Some machines were not designed to allow for any communication, and while others provided only partial communications that presume a person is operating the front panel. The few machines that were designed to be integrated into a system were rarely compatible, even within a single vendor. At least one dream for factory automation should be simple: Roll a computer onto a factory floor; plug it into a set ...

He points out that one of the key features these systems lack is "a suitable verification methodology or a technique for testing the consistency and completeness of a rule set." It is precisely this feature that we address here. LES is a generic rule-based expert system building tool (Laffey, Perkins, and Nguyen 1986) similar to EMYCIN (Van Melle 1981) that has been used as a framework to construct expert systems in many areas, such as electronic equipment diagnosis, design verification, photointerpretation, and hazard analysis. LES represents factual data in its frame database and heuristic and control knowledge in its production rules. LES allows the knowledge engineer to use both data-driven and goaldriven rules.

TACAIR-SOAR flew all U.S. fixed-wing aircraft. The general goal was to generate behavior that "looks human" when viewed by a training audience participating in operational military exercises. Its most dramatic use was in the Synthetic Theater of War 1997 (STOW '97), held 29-31 October 1997 (Ceranowicz, 1998; Laird, Jones, and Nielsen 1998; Laird et al. 1998). STOW '97 was a United States Department of Defense (DoD) Advanced Concept Technology Demonstration (ACTD) that was integrated with the United Endeavor 98-1 (UE 98-1) training exercise. As an ACTD, the overall goal of STOW '97 was to permit an early and inexpensive evaluation of advanced technologies that show promise for improving military effectiveness.

Static knowledge about gait and anatomy is represented in frames and dynamic evaluation strategies are represented in frames and metarules. Initial results are described by Dzierzanowski et al. (Dzierzanowski et al., 1983). We have completed several expert systems for electroencephalogram evaluation (Jagannathan, et al., 1981, 1982) (Bourne et al., A rule-based consultant system has been implemented for advising physicians about the prescription of initial dialysis therapies (Schaffer et al, 1983). This system is now in use at the Dialysis Clinics, Inc., Nashville, Tennessee. This system is now being expanded into a community of simulated consultative experts that provide advice about pharmacology, cardiovascular problems, nutrition and other problems Personnel: J. D. Schaffer, J. Cavaedes, J Bourne This project is devoted to building a complete system that assists the electromyogram [EMG] reader.

For more detailed information about any of MITRE's projects please contact Joseph Katz (KATZQMITRE-Bedford) or Richard Brown CLINUS!BROWN@MITRE-Bedford) at the Bedford center or Peter 6onasso (BONASSOQMITRE) at the Washington center Subsequently, Rome Air Development Center took over support of the project and continues to fund part of our AI research effort. MITRE's current research is summarized below. The Bedford center is supported by 15 Symbolics Lisp machines netted to two Vax-780 file servers, while the Washington center is supported by both a classified and an unclassified facility, with 2 Lambdas and 2 Symbolics Lisp machines respectively netted to Vax-780 file servers. Both centers support creative groups of people who generate exciting new ideas. Planning MITRE Bedford AI Programs and Reasoning Research into planning and reasoning started with the development of the KNOBS system.