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Knowledge base rule partitioning design for CLIPS

This describes a knowledge base (KB) partitioning approach to solve the problem of real-time performance using the CLIPS AI shell when containing large numbers of rules and facts. This work is funded under the joint USAF/NASA Advanced Launch System (ALS) Program as applied research in expert systems to perform vehicle checkout for real-time controller and diagnostic monitoring tasks. The Expert System advanced development project (ADP-2302) main objective is to provide robust systems responding to new data frames of 0.1 to 1.0 second intervals. The intelligent system control must be performed within the specified real-time window, in order to meet the demands of the given application. Partitioning the KB reduces the complexity of the inferencing Rete net at any given time. This reduced complexity improves performance but without undo impacts during load and unload cycles. The second objective is to produce highly reliable intelligent systems. This requires simple and automated approaches to the KB verification & validation task. Partitioning the KB reduces rule interaction complexity overall. Reduced interaction simplifies the V&V testing necessary by focusing attention only on individual areas of interest. Many systems require a robustness that involves a large number of rules, most of which are mutually exclusive under different phases or conditions. The ideal solution is to control the knowledge base by loading rules that directly apply for that condition, while stripping out all rules and facts that are not used during that cycle. The practical approach is to cluster rules and facts into associated 'blocks'. A simple approach has been designed to control the addition and deletion of 'blocks' of rules and facts, while allowing real-time operations to run freely. Timing tests for real-time performance for specific machines under R/T operating systems have not been completed but are planned as part of the analysis process to validate the design.

Mainardi, Joseph D.

Design Rules for Life Support Systems

This paper considers some of the common assumptions and engineering rules of thumb used in life support system design. One general design rule is that the longer the mission, the more the life support system should use recycling and regenerable technologies. A more specific rule is that, if the system grows more than half the food, the food plants will supply all the oxygen needed for the crew life support. There are many such design rules that help in planning the analysis of life support systems and in checking results. These rules are typically if-then statements describing the results of steady-state, "back of the envelope," mass flow calculations. They are useful in identifying plausible candidate life support system designs and in rough allocations between resupply and resource recovery. Life support system designers should always review the design rules and make quick steady state calculations before doing detailed design and dynamic simulation. This paper develops the basis for the different assumptions and design rules and discusses how they should be used. We start top-down, with the highest level requirement to sustain human beings in a closed environment off Earth. We consider the crew needs for air, water, and food. We then discuss atmosphere leakage and recycling losses. The needs to support the crew and to make up losses define the fundamental life support system requirements. We consider the trade-offs between resupplying and recycling oxygen, water, and food. The specific choices between resupply and recycling are determined by mission duration, presence of in-situ resources, etc., and are defining parameters of life support system design.

Jones, Harry

Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems

Mathematically sound techniques are used to view a knowledge-based system (KBS) as a set of processes executing in parallel and being enabled in response to specific rules being fired. The set of processes can be manipulated, examined, analyzed, and used in a simulation. The tool that embodies this technology may warn developers of errors in their rules, but may also highlight rules (or sets of rules) in the system that are underspecified (or overspecified) and need to be corrected for the KBS to operate as intended. The rules embodied in a KBS specify the allowed situations, events, and/or results of the system they describe. In that sense, they provide a very abstract specification of a system. The system is implemented through the combination of the system specification together with an appropriate inference engine, independent of the algorithm used in that inference engine. Viewing the rule base as a major component of the specification, and choosing an appropriate specification notation to represent it, reveals how additional power can be derived from an approach to the knowledge-base system that involves analysis, simulation, and verification. This innovative approach requires no special knowledge of the rules, and allows a general approach where standardized analysis, verification, simulation, and model checking techniques can be applied to the KBS.

Hinchey, Mike

A Mathematical Analysis of Air Traffic Priority Rules

This paper analyzes priority rules, such as those in Part 91.113 of the Federal Aviation Regulations. Such rules determine which of two aircraft should maneuver in a given conflict scenario. While the rules in 91.113 are well accepted, other concepts of operation for NextGen, such as self separation, may allow for different priority rules. A mathematical framework is presented that can be used to analyze a general set of priority rules and enables proofs of important properties. Specific properties considered in this paper include safety, effectiveness, and stability. A set of rules is said to be safe if it ensures that it is never the case that both aircraft have priority. They are effective if exactly one aircraft has priority in every situation. Finally, a set of rules is called stable if it produces compatible results even under small changes to input data.

Nakawicz, Anthony J.

Updates to NASA’s Break-in-Prebreathe Rules Due to Type II Decompression Sickness Risk Considerations

INTRODUCTION. Investigation of a central neurological decompression sickness (DCS) case during ground testing at Johnson Space Center identified a break-in-prebreathe (BIP) 13 minutes prior to depressurization as the leading credible cause despite applicable prebreathe payback rules being followed. Applicable NASA rules, for ground and flight, directed 2:1 payback of breaks up to 10 mins in duration, regardless of when a break occurs relative to depress. Full restart of prebreathe is directed following breaks > 10 min. The adequacy of NASA’s BIP rules was evaluated prior to resuming hypobaric ground testing or ISS extravehicular activities. METHODS. The following information sources were reviewed prior to formulating recommendations: i) Type II DCS case report and investigation findings; ii) documented rationale for existing flight rules, iii) consultations with subject matter experts involved in definition of existing flight rules (several of whom had since left NASA), iv) relevant published literature, v) model estimates of tissue on-gassing and off-gassing, and vi) NASA’s operational experience with late breaks in prebreathe. RESULTS. NASA’s nominal prebreathe protocols are validated via extensive ground testing to ensure DCS risk is reduced to within acceptable limits. Conversely, there exists a paucity of data, no validated models, and limited documentation regarding BIP risk for NASA prebreathe protocols. Flight rules implemented for shuttle and later ISS are based primarily on expert opinion and an assumption of symmetric on-gassing and off-gassing, which would make 2:1 payback a conservative mitigation for a BIP. Assumption of exponential gas kinetics makes late breaks higher risk, or require greater payback, than earlier breaks. Two BIPs have occurred using the current ISS prebreathe protocol, each of which was followed by greater than 2:1 payback and at least 59 minutes of 100% O2 pre-depress. No DCS cases have been reported during shuttle or ISS EVA operations. DISCUSSION. Interim changes were implemented to protect against late breaks during ground and flight prebreathes by ensuring negligible difference in conservatively modeled ppN2 pre-depress compared to nominal validated protocols. Additional documentation and literature review as well as chamber test planning are ongoing with the objective of further ground and flight rule updates and validation of a BIP risk model.

Prebreathe

Updates to NASA’s Break-in-Prebreathe Rules Due to Type II Decompression Sickness Risk Considerations

INTRODUCTION. Investigation of a central neurological decompression sickness (DCS) case during ground testing at Johnson Space Center identified a break-in-prebreathe (BIP) 13 minutes prior to depressurization as the leading credible cause despite applicable prebreathe payback rules being followed. Applicable NASA rules, for ground and flight, directed 2:1 payback of breaks up to 10 mins in duration, regardless of when a break occurs relative to depress. Full restart of prebreathe is directed following breaks > 10 min. The adequacy of NASA’s BIP rules was evaluated prior to resuming hypobaric ground testing or ISS extravehicular activities. METHODS. The following information sources were reviewed prior to formulating recommendations: i) Type II DCS case report and investigation findings; ii) documented rationale for existing flight rules, iii) consultations with subject matter experts involved in definition of existing flight rules (several of whom had since left NASA), iv) relevant published literature, v) model estimates of tissue on-gassing and off-gassing, and vi) NASA’s operational experience with late breaks in prebreathe. RESULTS. NASA’s nominal prebreathe protocols are validated via extensive ground testing to ensure DCS risk is reduced to within acceptable limits. Conversely, there exists a paucity of data, no validated models, and limited documentation regarding BIP risk for NASA prebreathe protocols. Flight rules implemented for shuttle and later ISS are based primarily on expert opinion and an assumption of symmetric on-gassing and off-gassing, which would make 2:1 payback a conservative mitigation for a BIP. Assumption of exponential gas kinetics makes late breaks higher risk, or require greater payback, than earlier breaks. Two BIPs have occurred using the current ISS prebreathe protocol, each of which was followed by greater than 2:1 payback and at least 59 minutes of 100% O2 pre-depress. No DCS cases have been reported during shuttle or ISS EVA operations. DISCUSSION. Interim changes were implemented to protect against late breaks during ground and flight prebreathes by ensuring negligible difference in conservatively modeled ppN2 pre-depress compared to nominal validated protocols. Additional documentation and literature review as well as chamber test planning are ongoing with the objective of further ground and flight rule updates and validation of a BIP risk model.

Prebreathe

Apollo experience report: The role of flight mission rules in mission preparation and conduct

The development of flight mission rules from the mission development phase through the detailed mission-planning phase and through the testing and training phase is analyzed. The procedure for review of the rules and the coordination requirements for mission-rule development are presented. The application of the rules to real-time decision making is outlined, and consideration is given to the benefit of training ground controllers and flightcrews in the methods of determining the best response to a nonnominal in-flight situation for which no action has been preplanned. The Flight Mission Rules document is discussed in terms of the purpose and objective thereof and in terms of the definition, the development, and the use of mission rules.

Keyser, L. W.

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.

SIRE: A Simple Interactive Rule Editor for NICBES

To support evolution of domain expertise, and its representation in an expert system knowledge base, a user-friendly rule base editor is mandatory. The Nickel Cadmium Battery Expert System (NICBES), a prototype of an expert system for the Hubble Space Telescope power storage management system, does not provide such an editor. In the following, a description of a Simple Interactive Rule Base Editor (SIRE) for NICBES is described. The SIRE provides a consistent internal representation of the NICBES knowledge base. It supports knowledge presentation and provides a user-friendly and code language independent medium for rule addition and modification. The SIRE is integrated with NICBES via an interface module. This module provides translation of the internal representation to Prolog-type rules (Horn clauses), latter rule assertion, and a simple mechanism for rule selection for its Prolog inference engine.

Bykat, Alex

Importance of rule groupings in verification of expert systems

This paper elaborates attempts to semiautomatically structure a CLIPS expert-system rule base into groups of related rules that carry the same type of information. Different distance metrics that capture relevant information from the rules for grouping are discussed. Two clustering algorithms that partition the rule base into groups of related rules are given. Two independent evaluation criteria are developed to measure the effectiveness of the grouping strategies. Results of an experiment with three sample rule bases are presented.

Mehrotra, Mala

A rule-based software test data generator

Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100,000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further.

Deason, William H.

An Embedded Rule-Based Diagnostic Expert System in Ada

Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

Jones, Robert E.

Rule groupings in expert systems

Currently, expert system shells do not address software engineering issues for developing or maintaining expert systems. As a result, large expert systems tend to be incomprehensible, difficult to debug or modify, and almost impossible to verify or validate Partitioning rule-based systems into rule groups which reflect the underlying subdomains of the problem should enhance the comprehensibility, maintainability, and reliability of expert-system software. In this paper, we investigate methods to semi-automatically structure a CLIPS rule base e into groups of rules that carry related information. We discuss three different distance metrics for measuring the relatedness of rules and describe two clustering algorithms based on these distance metrics. The results of our experiment with three sample rule bases are also presented.

Mehrotra, Mala

Supersonic and Moment-of-Area Rules Combined for Rapid Zero-Lift Wave-Drag Calculations

The concepts of the supersonic area rule and the moment-of-area rule are combined to develop a new method for calculating zero-lift wave drag which is amenable to the use of ordinary desk calculators. The total zero-lift wave drag of a configuration is calculated by the new method as the sum of the wave drag of each component alone plus the interference between components. In calculating the separate contributions each component or pair of components is analyzed over the smallest allowable length in order to improve the convergence of the series expression for the wave drag. The accuracy of the present method is evaluated by comparing the total zero-lift wave-drag solutions for several simplified configurations obtained by the present method with solutions given by slender-body and linearized theory. The accuracy and computational time required by the present method are also evaluated relative to the supersonic area rule and the moment-of-area rule. The results of the evaluation indicate that total zero-lift wave-drag solutions for simplified configurations can be obtained by the present method which differ from solutions given by slender-body and linearized theory by less than 6 percent. This accuracy for simplified configurations was obtained from only nine terms of the series expression for the wave drag as a result of calculating the total zero-lift wave drag by parts. For the same number of terms these results represent an accuracy greater than that for solutions obtained by either of the two methods upon which the present method is based, except in a few isolated cases. For the excepted cases, solutions by the present method and the supersonic area rule are identical. Solutions by the present method are obtained in one fifth the computing time required by the supersonic area rule. This difference in computing time of course would be substantially reduced if the complete procedures for both methods were programmed on electronic computing machines.

Levy, Lionel L., Jr.

On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

Tunstel, Edward

Refining Linear Fuzzy Rules by Reinforcement Learning

Linear fuzzy rules are increasingly being used in the development of fuzzy logic systems. Radial basis functions have also been used in the antecedents of the rules for clustering in product space which can automatically generate a set of linear fuzzy rules from an input/output data set. Manual methods are usually used in refining these rules. This paper presents a method for refining the parameters of these rules using reinforcement learning which can be applied in domains where supervised input-output data is not available and reinforcements are received only after a long sequence of actions. This is shown for a generalization of radial basis functions. The formation of fuzzy rules from data and their automatic refinement is an important step in closing the gap between the application of reinforcement learning methods in the domains where only some limited input-output data is available.

Berenji, Hamid R.

Conformance Testing: Measurement Decision Rules

The goal of a Quality Management System (QMS) as specified in ISO 9001 and AS9100 is to provide assurance to the customer that end products meet specifications. Measuring devices, often called measuring and test equipment (MTE), are used to provide the evidence of product conformity to specified requirements. Unfortunately, processes that employ MTE can become a weak link to the overall QMS if proper attention is not given to the measurement process design, capability, and implementation. Documented "decision rules" establish the requirements to ensure measurement processes provide the measurement data that supports the needs of the QMS. Measurement data are used to make the decisions that impact all areas of technology. Whether measurements support research, design, production, or maintenance, ensuring the data supports the decision is crucial. Measurement data quality can be critical to the resulting consequences of measurement-based decisions. Historically, most industries required simplistic, one-size-fits-all decision rules for measurements. One-size-fits-all rules in some cases are not rigorous enough to provide adequate measurement results, while in other cases are overly conservative and too costly to implement. Ideally, decision rules should be rigorous enough to match the criticality of the parameter being measured, while being flexible enough to be cost effective. The goal of a decision rule is to ensure that measurement processes provide data with a sufficient level of quality to support the decisions being made - no more, no less. This paper discusses the basic concepts of providing measurement-based evidence that end products meet specifications. Although relevant to all measurement-based conformance tests, the target audience is the MTE end-user, which is anyone using MTE other than calibration service providers. Topics include measurement fundamentals, the associated decision risks, verifying conformance to specifications, and basic measurement decisions rules.

Mimbs, Scott M.

Cassini Attitude Control Operations Flight Rules and How They are Enforced

The Cassini spacecraft was launched on October 15, 1997 and arrived at Saturn on June 30, 2004. It has performed detailed observations and remote sensing of Saturn, its rings, and its satellites since that time. Cassini deployed the European-built Huygens probe which descended through the Titan atmosphere and landed on its surface on January 14, 2005. Operating the Cassini spacecraft is a complex scientific, engineering, and management job. In order to safely operate the spacecraft, a large number of flight rules were developed. These flight rules must be enforced throughout the lifetime of the Cassini spacecraft. Flight rules are defined as any operational limitation imposed by the spacecraft system design, hardware, and software, violation of which would result in spacecraft damage, loss of consumables, loss of mission objectives, loss and/or degradation of science, and less than optimal performance. Flight rules require clear description and rationale. Detailed automated methods have been developed to insure the spacecraft is continuously operated within these flight rules. An overview of all the flight rules allocated to the Cassini Attitude Control and Articulation Subsystem and how they are enforced is presented in this paper.

Burk, Thomas