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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

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NASA NTRS1989

Expert systems should be more accurate than human experts - Evaluation procedures from human judgment and decisionmaking

Two procedures for the evaluation of the performance of expert systems are illustrated: one procedure evaluates predictive accuracy; the other procedure is complementary in that it uncovers the factors that contribute to predictive accuracy. Using these procedures, it is argued that expert systems should be more accurate than human experts in two senses. One sense is that expert systems must be more accurate to be cost-effective. Previous research is reviewed and original results are presented which show that simple statistical models typically perform better than human experts for the task of combining evidence from a given set of information sources. The results also suggest the second sense in which expert systems should be more accurate than human experts. They reveal that expert systems should share factors that contribute to human accuracy, but not factors that detract from human accuracy. Thus the thesis is that one should both require and expect systems to be more accurate than humans.

Levi, Keith↗

NASA NTRS1987

Expert systems built by the Expert: An evaluation of OPS5

Two expert systems were written in OPS5 by the expert, a Ph.D. astronomer with no prior experience in artificial intelligence or expert systems, without the use of a knowledge engineer. The first system was built from scratch and uses 146 rules to check for duplication of scientific information within a pool of prospective observations. The second system was grafted onto another expert system and uses 149 additional rules to estimate the spacecraft and ground resources consumed by a set of prospective observations. The small vocabulary, the IF this occurs THEN do that logical structure of OPS5, and the ability to follow program execution allowed the expert to design and implement these systems with only the data structures and rules of another OPS5 system as an example. The modularity of the rules in OPS5 allowed the second system to modify the rulebase of the system onto which it was grafted without changing the code or the operation of that system. These experiences show that experts are able to develop their own expert systems due to the ease of programming and code reusability in OPS5.

Jackson, Robert↗

NASA NTRS1994

Expert Witness: A system for developing expert medical testimony

Expert Witness in an expert system designed to assist attorneys and medical experts in determining the merit of medical malpractice claims in the area of obstetrics. It substitutes the time of the medical expert with the time of a paralegal assistant guided by the expert system during the initial investigation of the medical records and patient interviews. The product of the system is a narrative transcript containing important data, immediate conclusions from the data, and overall conclusions of the case that the attorney and medical expert use to make decisions about whether and how to proceed with the case. The transcript may also contain directives for gathering additional information needed for the case. The system is a modified heuristic classifier and is implemented using over 600 CLIPS rules together with a C-based user interface. The data abstraction and solution refinement are implemented directly using forward chaining production and matching. The use of CLIPS and C is essential to delivering a system that runs on a generic PC platform. The direct implementation in CLIPS together with locality of inference ensures that the system will scale gracefully. Two years of use has revealed no errors in the reasoning.

Lewandowski, Raymond↗

NASA NTRS1990

Techniques for capturing expert knowledge - An expert systems/hypertext approach

The knowledge-acquisition strategy developed for the Explosive Hazards Classification (EHC) Expert System is described in which expert systems and hypertext are combined, and broad applications are proposed. The EHC expert system is based on rapid prototyping in which primary knowledge acquisition from experts is not emphasized; the explosive hazards technical bulletin, technical guidance, and minimal interviewing are used to develop the knowledge-based system. Hypertext is used to capture the technical information with respect to four issues including procedural, materials, test, and classification issues. The hypertext display allows the integration of multiple knowlege representations such as clarifications or opinions, and thereby allows the performance of a broad range of tasks on a single machine. Among other recommendations, it is suggested that the integration of hypertext and expert systems makes the resulting synergistic system highly efficient.

Lafferty, Larry↗

NASA NTRS1989

Equating an expert system to a classifier in order to evaluate the expert system

A strategy to evaluate an expert system is formulated. The strategy proposed is based on finding an equivalent classifier to an expert system and evaluate that classifier with respect to an optimal classifier, a Bayes classifier. Here it is shown that for the rules considered an equivalent classifier exists. Also, a brief consideration of meta and meta-meta rules is included. Also, a taxonomy of expert systems is presented and an assertion made that an equivalent classifier exists for each type of expert system in the taxonomy with associated sets of underlying assumptions.

Odell, Patrick L.↗

NASA NTRS1992

Fault isolation detection expert (FIDEX). Part 1: Expert system diagnostics for a 30/20 Gigahertz satellite transponder

LeRC has recently completed the design of a Ka-band satellite transponder system, as part of the Advanced Communication Technology Satellite (ACTS) System. To enhance the reliability of this satellite, NASA funded the University of Akron to explore the application of an expert system to provide the transponder with an autonomous diagnosis capability. The results of this research was the development of a prototype diagnosis expert system called FIDEX (fault-isolation and diagnosis expert). FIDEX is a frame-based expert system that was developed in the NEXPERT Object development environment by Neuron Data, Inc. It is a MicroSoft Windows version 3.0 application, and was designed to operate on an Intel i80386 based personal computer system.

Durkin, John↗

NASA NTRS1992

Ground terminal expert (GTEX). Part 2: Expert system diagnostics for a 30/20 Gigahertz satellite transponder

A research effort was undertaken to investigate how expert system technology could be applied to a satellite communications system. The focus of the expert system is the satellite earth station. A proof of concept expert system called the Ground Terminal Expert (GTEX) was developed at the University of Akron in collaboration with the NASA Lewis Research Center. With the increasing demand for satellite earth stations, maintenance is becoming a vital issue. Vendors of such systems will be looking for cost effective means of maintaining such systems. The objective of GTEX is to aid in diagnosis of faults occurring with the digital earth station. GTEX was developed on a personal computer using the Automated Reasoning Tool for Information Management (ART-IM) developed by the Inference Corporation. Developed for the Phase 2 digital earth station, GTEX is a part of the Systems Integration Test and Evaluation (SITE) facility located at the NASA Lewis Research Center.

Durkin, John↗

NASA NTRS2017

Ask-the-expert: Active Learning Based Knowledge Discovery Using the Expert

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the backend. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning.

software↗

NASA NTRS2017

Ask-the-Expert: Active Learning Based Knowledge Discovery Using the Expert

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the back end. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning.

GUI↗

NASA NTRS1996

A Generic Expert Scheduling System Architecture and Toolkit: GUESS (Generically Used Expert Scheduling System)

Scheduling has become an increasingly important element in today's society and workplace. Within the NASA environment, scheduling is one of the most frequently performed and challenging functions. Towards meeting NASA's scheduling needs, a research version of a generic expert scheduling system architecture and toolkit has been developed. This final report describes the development and testing of GUESS (Generically Used Expert Scheduling System).

Liebowitz, Jay↗

NASA NTRS1987

Interfacing the expert: Characteristics and requirements for the user interface in expert systems

Because expert systems deal with new sets of problems presenting unique interface requirements, special issues requiring special attention are presented to user interface designers. External knowledge representation (how knowdedge is represented across the user interface), modes of user-system interdependence (advisory, cooperative, and autonomous), and management of uncertainty (deciding what actions to take or recommend based on incomplete evidence) are discussed.

Potter, Andrew↗

NASA NTRS1988

Successful expert systems for space shuttle payload integration

Expert systems are successfully applied to solve recurring NASA Space Shuttle orbiter payload integration problems. Recurrence of these problems is the result of each Space Shuttle mission being unique. The NASA Space Shuttle orbiter was designed to be extremely flexible in its ability to handle many types and combinations of satellites and experiments. This flexibility results in different and unique engineering resource requirements for each of the payload satellites and experiments. The first successful expert system to be applied to these problems was the Orbiter Payload Bay Cabling Expert System (EXCABL), developed at Rockwell International Space Transportation Systems Division. The operational version of EXCABL was delivered in 1986 and successfully solved the payload electrical support services cabling layout problem. As a result of this success, a second expert system, Expert Drawing Matching System (EXMATCH), was developed to generate a list of the reusable installation drawings available for each EXCABL solution. EXMATCH went operational in 1987. As a result of these initial successes, the need for a third expert system was defined and is awaiting development. This new Expert System, called Technical Order Listing Expert System (EXTOL), will generate a list of all the applicable reusable installation drawings available to support the total payload bay mission provisioning and installation effort. This paper describes these expert systems, the individual problems that they were designed to solve, their individual solutions, and the degree of success achieved. These expert systems' instantiate the applicability of this technology to the solution of real-world Space Shuttle payload integration problems.

Morris, Keith↗

NASA NTRS1988

The emergence of multi-user expert systems

There exists a set of problems for which the single user workstation is not a viable solution. In some cases, it may be necessary for the system to support numerous experts working on different aspects of a single logical activity concurrently. In others, the activity may extend over a prolonged period of time during which different experts will work on different phases of the project to produce a single integrated result. Another possibility is that the results produced by the expert system must be continuously available to some group other than that actively exercising the expert system. These are the types of applications which require multiuser expert systems. The nature of NASA tends to produce expert system domains which are inherently multiuser. It is these domains that this new class of expert systems has first been encountered. As expert systems move into the main stream of large scale engineering projects, these encounters will become more frequent. A need for expert system building tools which can accommodate the unique properties of these multiuser domains as they emerge is a problem which needs to be addressed as the current set of tools migrate to time sharing environments, and as new tools are developed.

Freeman, Michael S.↗

NASA NTRS1991

Utilizing expert systems for satellite monitoring and control

Spacecraft analysts in the spacecraft control center for the Cosmic Background Explorer (COBE) satellite are currently utilizing a fault-isolation expert system developed to assist in the isolation and correction of faults in the communications link. This system, the communication link expert assistance resource (CLEAR), monitors real time spacecraft and ground systems performance parameters in search of configuration discrepancies and communications link problems. If such a discrepancy or problem is isolated, CLEAR alerts the analyst and provides advice on how to resolve the problem swiftly and effectively. The CLEAR system is the first real time expert system to be used in the operational environment of a satellite control center at the NASA Goddard Space Flight Center. Clear has not only demonstrated the utility and potential of an expert system in the demanding environment of a satellite control center, but also has revealed many of the pitfalls and deficiencies of development of expert systems. One of the lessons learned from this and other initial expert system projects is that prototypes can often be developed quite rapidly, but operational expert systems require considerable effort. Development is generally a slow, tedious process that typically requires the special skills of trained programmers. Due to the success of CLEAR and several other systems in the control center domain, a large number of expert systems will certainly be developed to support control center operations during the early 1990's. To facilitate the development of these systems, a project was initiated to develop an integrated, domain-specific tool, the generic spacecraft analyst assistent (GenSAA), that alows the spacecraft analysts to rapidly create simple expert systems themselves. By providing a highly graphical point-and-select method of system development, GenSAA allows the analyst to utilize and/or modify previously developed rule bases and system components; thus, facilitating software reuse and reducing development time and effort.

Hughes, Peter M.↗

NASA NTRS1991

Validation of an expert system intended for research in distributed artificial intelligence

The expert system discussed in this paper is designed to function as a testbed for research on cooperating expert systems. Cooperating expert systems are members of an organization which dictates the manner in which the expert systems will interact when solving a problem. The Blackbox Expert described in this paper has been constructed using the C Language Integrated Production System (CLIPS), C++, and X windowing environment. CLIPS is embedded in a C++ program which provides objects that are used to maintain the state of the Blackbox puzzle. These objects are accessed by CLIPS rules through user-defined functions calls. The performance of the Blackbox Expert is validated by experimentation. A group of people are asked to solve a set of test cases for the Blackbox puzzle. A metric has been devised which evaluates the 'correctness' of a solution proposed for a test case of Blackbox. Using this metric and the solutions proposed by the humans, each person receives a rating for their ability to solve the Blackbox puzzle. The Blackbox Expert solves the same set of test cases and is assigned a rating for its ability. Then the rating obtained by the Blackbox Expert is compared with the ratings of the people, thus establishing the skill level of our expert system.

Grossner, C.↗

NASA NTRS1990

Three CLIPS-based expert systems for solving engineering problems

We have written three expert systems, using the CLIPS PC-based expert system shell. These three expert systems are rule based and are relatively small, with the largest containing slightly less than 200 rules. The first expert system is an expert assistant that was written to help users of the ASPEN computer code choose the proper thermodynamic package to use with their particular vapor-liquid equilibrium problem. The second expert system was designed to help petroleum engineers choose the proper enhanced oil recovery method to be used with a given reservoir. The effectiveness of each technique is highly dependent upon the reservoir conditions. The third expert system is a combination consultant and control system. This system was designed specifically for silicon carbide whisker growth. Silicon carbide whiskers are an extremely strong product used to make ceramic and metal composites. The manufacture of whiskers is a very complicated process. which to date. has defied a good mathematical model. The process was run by experts who had gained their expertise by trial and error. A system of rules was devised by these experts both for procedure setup and for the process control. In this paper we discuss the three problem areas of the design, development and evaluation of the CLIPS-based programs.

Parkinson, W. J.↗

NASA NTRS1987

Expert system technology

The expert system is a computer program which attempts to reproduce the problem-solving behavior of an expert, who is able to view problems from a broad perspective and arrive at conclusions rapidly, using intuition, shortcuts, and analogies to previous situations. Expert systems are a departure from the usual artificial intelligence approach to problem solving. Researchers have traditionally tried to develop general modes of human intelligence that could be applied to many different situations. Expert systems, on the other hand, tend to rely on large quantities of domain specific knowledge, much of it heuristic. The reasoning component of the system is relatively simple and straightforward. For this reason, expert systems are often called knowledge based systems. The report expands on the foregoing. Section 1 discusses the architecture of a typical expert system. Section 2 deals with the characteristics that make a problem a suitable candidate for expert system solution. Section 3 surveys current technology, describing some of the software aids available for expert system development. Section 4 discusses the limitations of the latter. The concluding section makes predictions of future trends.

Prince, Mary Ellen↗

NASA NTRS1988

MOORE: A prototype expert system for diagnosing spacecraft problems

MOORE is a rule-based, prototype expert system that assists in diagnosing operational Tracking and Data Relay Satellite (TDRS) problems. It is intended to assist spacecraft engineers at the TDRS ground terminal in trouble shooting problems that are not readily solved with routine procedures, and without expert counsel. An additional goal of the prototype system is to develop in-house expert system and knowledge engineering skills. The prototype system diagnoses antenna pointing and earth pointing problems that may occur within the TDRS Attitude Control System (ACS). Plans include expansion to fault isolation of problems in the most critical subsystems of the TDRS spacecraft. Long term benefits are anticipated with use of an expert system during future TDRS programs with increased mission support time, reduced problem solving time, and retained expert knowledge and experience. Phase 2 of the project is intended to provide NASA the necessary expertise and capability to define requirements, evaluate proposals, and monitor the development progress of a highly competent expert system for NASA's Tracking Data Relay Satellite. Phase 2 also envisions addressing two unexplored applications for expert systems, spacecraft integration and tests (I and T) and support to launch activities. The concept, goals, domain, tools, knowledge acquisition, developmental approach, and design of the expert system. It will explain how NASA obtained the knowledge and capability to develop the system in-house without assistance from outside consultants. Future plans will also be presented.

Howlin, Katherine↗