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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

A logical model of cooperating rule-based systems

A model is developed to assist in the planning, specification, development, and verification of space information systems involving distributed rule-based systems. The model is based on an analysis of possible uses of rule-based systems in control centers. This analysis is summarized as a data-flow model for a hypothetical intelligent control center. From this data-flow model, the logical model of cooperating rule-based systems is extracted. This model consists of four layers of increasing capability: (1) communicating agents, (2) belief-sharing knowledge sources, (3) goal-sharing interest areas, and (4) task-sharing job roles.

Bailin, Sidney C.↗
NASA NTRS1989

A logical model of cooperating rule-based systems in space mission ground support facilities

This paper describes an abstract reference model of cooperating rule-based systems (CRBSs). The model is intended to assist in the planning, specification, development, and verification of space information systems involving multiple, distributed, communicating rule-based systems. The functions performed in ground control systems are described, and five types of rule-based systems that could be used in such centers are identified. The interactions between rule-based systems are examined, and the unique requirements of such systems are addressed. A four-layer logical model is discussed which provides a framework for discussing solutions to unique CRBS requirements. The elements and operations at each layer are described.

Bailin, Sidney C.↗
NASA NTRS1988

A rule-based systems approach to spacecraft communications configuration optimization

An experimental rule-based system for optimizing user spacecraft communications configurations was developed at NASA to support mission planning for spacecraft that obtain telecommunications services through NASA's Tracking and Data Relay Satellite System. Designated Expert for Communications Configuration Optimization (ECCO), and implemented in the OPS5 production system language, the system has shown the validity of a rule-based systems approach to this optimization problem. The development of ECCO and the incremental optimization method on which it is based are discussed. A test case using hypothetical mission data is included to demonstrate the optimization concept.

Rash, James L.↗
NASA NTRS1988

A rule-based systems approach to spacecraft communications configuration optimization

An experimental rule-based system for optimizing user spacecraft communications configurations was developed at NASA to support mission planning for spacecraft that obtain telecommunications services through NASA's Tracking and Data Relay Satellite System. Designated Expert for Communications Configuration Optimization (ECCO), and implemented in the OPS5 production system language, the system has shown the validity of a rule-based systems approach to this optimization problem. The development of ECCO and the incremental optimizatin method on which it is based are discussed. A test case using hypothetical mission data is included to demonstrate the optimization concept.

Rash, James L.↗
NASA NTRS1990

Integration of object-oriented knowledge representation with the CLIPS rule based system

The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

Logie, David S.↗
NASA NTRS1990

An architecture for rule based system explanation

A system architecture is presented which incorporate both graphics and text into explanations provided by rule based expert systems. This architecture facilitates explanation of the knowledge base content, the control strategies employed by the system, and the conclusions made by the system. The suggested approach combines hypermedia and inference engine capabilities. Advantages include: closer integration of user interface, explanation system, and knowledge base; the ability to embed links to deeper knowledge underlying the compiled knowledge used in the knowledge base; and allowing for more direct control of explanation depth and duration by the user. User models are suggested to control the type, amount, and order of information presented.

Fennel, T. R.↗
NASA NTRS1986

Simple methods of exploiting the underlying structure of rule-based systems

Much recent work in the field of expert systems research has aimed at exploiting the underlying structures of the rule base for reasons of analysis. Such techniques as Petri-nets and GAGs have been proposed as representational structures that will allow complete analysis. Much has been made of proving isomorphisms between the rule bases and the mechanisms, and in examining the theoretical power of this analysis. In this paper we describe some early work in a new system which has much simpler (and thus, one hopes, more easily achieved) aims and less formality. The technique being examined is a very simple one: OPS5 programs are analyzed in a purely syntactic way and a FSA description is generated. In this paper we describe the technique and some user interface tools which exploit this structure.

Hendler, James↗
NASA NTRS1988

An approach to articulating expert system rule bases

A rule-base generation procedure is developed for expert systems used to diagnose anomalies in the performance of mechanical plants and similar engineering systems. The method is based on construction of a failure-mode information-propagation model (FIPM). Details of the FIPM procedure are discussed and illustrated with diagrams; reference is made to a sample application involving the turbopump of the high-pressure oxidizer for the Space Shuttle main engine.

Abernethy, Ken↗
NASA NTRS1990

Bounded-time fault-tolerant rule-based systems

Two systems concepts are introduced: bounded response-time and self-stabilization in the context of rule-based programs. These concepts are essential for the design of rule-based programs which must be highly fault tolerant and perform in a real time environment. The mechanical analysis of programs for these two properties is discussed. The techniques are used to analyze a NASA application.

Browne, James C.↗
NASA NTRS1992

A rule-based system for real-time analysis of control systems

An approach to automate the real-time analysis of flight critical health monitoring and system status is being developed and evaluated at the NASA Dryden Flight Research Facility. A software package was developed in-house and installed as part of the extended aircraft interrogation and display system. This design features a knowledge-base structure in the form of rules to formulate interpretation and decision logic of real-time data. This technique has been applied for ground verification and validation testing and flight testing monitoring where quick, real-time, safety-of-flight decisions can be very critical. In many cases post processing and manual analysis of flight system data are not required. The processing is described of real-time data for analysis along with the output format which features a message stack display. The development, construction, and testing of the rule-driven knowledge base, along with an application using the X-31A flight test program, are presented.

Larson, Richard R.↗
NASA NTRS1990

Building distributed rule-based systems using the AI Bus

The AI Bus software architecture was designed to support the construction of large-scale, production-quality applications in areas of high technology flux, running heterogeneous distributed environments, utilizing a mix of knowledge-based and conventional components. These goals led to its current development as a layered, object-oriented library for cooperative systems. This paper describes the concepts and design of the AI Bus and its implementation status as a library of reusable and customizable objects, structured by layers from operating system interfaces up to high-level knowledge-based agents. Each agent is a semi-autonomous process with specialized expertise, and consists of a number of knowledge sources (a knowledge base and inference engine). Inter-agent communication mechanisms are based on blackboards and Actors-style acquaintances. As a conservative first implementation, we used C++ on top of Unix, and wrapped an embedded Clips with methods for the knowledge source class. This involved designing standard protocols for communication and functions which use these protocols in rules. Embedding several CLIPS objects within a single process was an unexpected problem because of global variables, whose solution involved constructing and recompiling a C++ version of CLIPS. We are currently working on a more radical approach to incorporating CLIPS, by separating out its pattern matcher, rule and fact representations and other components as true object oriented modules.

Schultz, Roger D.↗
NASA NTRS1989

Reliability and performance evaluation of systems containing embedded rule-based expert systems

A method for evaluating the reliability of real-time systems containing embedded rule-based expert systems is proposed and investigated. It is a three stage technique that addresses the impact of knowledge-base uncertainties on the performance of expert systems. In the first stage, a Markov reliability model of the system is developed which identifies the key performance parameters of the expert system. In the second stage, the evaluation method is used to determine the values of the expert system's key performance parameters. The performance parameters can be evaluated directly by using a probabilistic model of uncertainties in the knowledge-base or by using sensitivity analyses. In the third and final state, the performance parameters of the expert system are combined with performance parameters for other system components and subsystems to evaluate the reliability and performance of the complete system. The evaluation method is demonstrated in the context of a simple expert system used to supervise the performances of an FDI algorithm associated with an aircraft longitudinal flight-control system.

Beaton, Robert M.↗
NASA NTRS1988

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Stclair, D. C.↗
NASA NTRS1991

Rule-based simulation models

Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

Nieten, Joseph L.↗
NASA NTRS1989

Applications of fuzzy sets to rule-based expert system development

Problems of implementing rule-based expert systems using fuzzy sets are considered. A fuzzy logic software development shell is used that allows inclusion of both crisp and fuzzy rules in decision making and process control problems. Results are given that compare this type of expert system to a human expert in some specific applications. Advantages and disadvantages of such systems are discussed.

Lea, Robert N.↗
NASA NTRS1989

Applications of fuzzy sets to rule-based expert system development

Problems of implementing rule-based expert systems using fuzzy sets are considered. A fuzzy logic software development shell is used that allows inclusion of both crisp and fuzzy rules indecision making and process control problems. Results are given that compare this type of expert system to a human expert in some specific applications. Advantages and disadvantages of such systems are discussed.

Lea, Robert N.↗
NASA NTRS1991

Rule groupings: An approach towards verification of expert systems

Knowledge-based expert systems are playing an increasingly important role in NASA space and aircraft systems. However, many of NASA's software applications are life- or mission-critical and knowledge-based systems do not lend themselves to the traditional verification and validation techniques for highly reliable software. Rule-based systems lack the control abstractions found in procedural languages. Hence, it is difficult to verify or maintain such systems. Our goal is to automatically structure a rule-based system into a set of rule-groups having a well-defined interface to other rule-groups. Once a rule base is decomposed into such 'firewalled' units, studying the interactions between rules would become more tractable. Verification-aid tools can then be developed to test the behavior of each such rule-group. Furthermore, the interactions between rule-groups can be studied in a manner similar to integration testing. Such efforts will go a long way towards increasing our confidence in the expert-system software. Our research efforts address the feasibility of automating the identification of rule groups, in order to decompose the rule base into a number of meaningful units.

Mehrotra, Mala↗