Tactical-level onboard real-time advisory expert systems for manned aircraft as development and maintenance entities

Tactical-level onboard intelligent systems support the crew’s decision-making concerning real-time targeting and determining the way of achieving real-time-assigned targets (tactical objectives). The classification and image of intelligent systems and their interactions with the crew and between each other, as well as knowledge of the replenishment procedures in the course of operation, are presented.     

Basic onboard real-time advisory system for a duel situation of distant air fight

The structure of the knowledge base of an onboard real-time advisory system for distant air fight 1 × 1 in which current information on the external situation is used for activation of one of the problem subsituations chosen from the total set of these subsituations is presented. Based on the analysis of the subject domain of distant air fight 1 × 1, four problem subsituations are formed: the problem subsituation no. 1 “taking the tactically advantageous position”; the problem subsituation no. 2 “attack”, the problem subsituation no. 3 “defense with attack”, and the problem subsituation no. 4 “defense”. For each of these subsituations on the basis of virtual simulation of the proposed development of the air fight and the corresponding set of production rules, the recommendations to the crew on rational method of its resolution are developed. The results of mathematical simulation of the operation of the onboard real-time advisory system for distant air fight 1 × 1 in the problem subsituation no. 2 are presented.     

A mathematical model of aircraft motion for knowledge bases of onboard online advisory expert systems

A model of the controlled motion of an aircraft as a point particle is described. The model is designated for real-time operation in knowledge bases of onboard advisory expert systems. The model implements a set of trajectory fragments which provides forming different trajectories of aircraft guidance to a target, antimissile, and free maneuvers. The model is parametrically adjusted to aerodynamic, mobile, and performance characteristics of a particular aircraft.     

Fuzzy concepts in an object oriented expert system shell

Fuzzy logic is one of the methods to model the vagueness and imprecision of human knowledge. Some rule-based expert system shells have been successfully developed and have demonstrated the power of fuzzy logic in dealing with inexact reasoning and rule inferences. However, using rules for knowledge representation is not structured enough. In addition, knowledge cannot be easily represented in an abstracted (hierarchical) from. In this article the introduction of fuzzy concepts into object oriented knowledge representation (OOKR), which is a structured knowledge representation scheme, is presented. A framework for handling all the possible fuzzy concepts in OOKR at both the dynamic and static levels is proposed. In order to handle the inheritance mechanism and to model the relations among classes, instances, and attributes, some new fuzzy concepts and operations are introduced. These concepts and operations are developed from the semantic meaning rather than by an ad hoc approach. A prototype of the expert system shell. System FX-I, has been successfully developed based on the above framework, showing the feasibility of handling inexact knowledge in a structural way.     

An explanation shell for expert systems

We describe a shell for expert systems written in Prolog. The shell provides a consultation environment and a range of explanation capabilities. The design of the shell is modular, making it very easy to extend the shell with extra features required by a particular expert system. The novelty of the shell is twofold. Firstly, it has a uniform design consisting of an integrated collection of meta-interpreters. Secondly, there is a new approach for explaining 'why not,' when a query to the system fails.     

A shell for cooperating expert systems

Abstract: This paper describes a shell for cooperating expert systems that has been developed at the University of Porto. The main goal of this shell is two-fold: to generate a community of cooperative knowledge-based systems and to develop several special reasoning techniques which can be used under a distributed and cooperative paradigm. UPShell is able to convert a set of generated intelligent systems (ISs) into a community of cooperative ISs. In this first version it is already possible to generate different intelligent systems which are able to run 'simultaneously' as separate Unix processes and, using a message-passing mechanism, to communicate among themselves. They can be set to pursue an overall goal in a cooperative way. Moreover, several tasks can be given to each IS to be solved simultaneously, and the IS can switch from task to task according to dynamic priorities reflecting the urgency attached to the specific sub-tasks that emerge. The shell described here may also be used to test, within a distributed environment, some time-bounded reasoning techniques that are presently being developed. The paper has three main parts: a general overview of the UPShell (Section 1); a tutorial explaining, by means of examples, how to use the package (Section 2); and, finally, some considerations on the reasoning techniques used and future improvements (Sections 3–5).     

A shell for signal interpretation expert systems

System monitoring and diagnosis through signal interpretation are important tasks in many engineering fields. Although monitoring or diagnosis expert systems help human experts a lot, it is not so easy to build a signal interpretation expert system. We have developed two expert systems for speech signal processing. The close analysis of the two systems revealed common functions and modules applicable to wide range of signal interpretation problems. On the basis of the experience, we have developed a shell for signal interpretation expert systems named SSI. In order to evaluate SSI, we also developed two expert systems by using it and obtained satisfactory results. This paper describes the design philosophy and architecture of SSI together with some examples.     

Constructing and consulting the knowledge base of an expert systems shell

Abstract: This paper presents an expert system shell whose inference mechanism uses backward chaining. In particular the modules devoted to constructing and consulting the knowledge base are illustrated. The programming environment is based on the Arity-Prolog language, a popular Prolog dialect running on IBM PCs and compatibles.     

Multiclass object classification for real-time video surveillance systems

Object classification in video is an important factor for improving the reliability of various automatic applications in video surveillance systems, as well as a fundamental feature for advanced applications, such as scene understanding. Despite extensive research, existing methods exhibit relatively moderate classification accuracy when tested on a large variety of real-world scenarios, or do not obey the real-time constraints of video surveillance systems. Moreover, their performance is further degraded in multi-class classification problems. We explore multi-class object classification for real-time video surveillance systems and propose an approach for classifying objects in both low and high resolution images (human height varies from a few to tens of pixels) in varied real-world scenarios. Firstly, we present several features that jointly leverage the distinction between various classes. Secondly, we provide a feature-selection procedure based on entropy gain, which screens out superfluous features. Experiments, using various classification techniques, were performed on a large and varied database consisting of ∼29,000 object instances extracted from 140 different real-world indoor and outdoor, near-field and far-field scenes having various camera viewpoints, which capture a large variety of object appearances under real-world environmental conditions. The insight raised from the experiments is threefold: the efficiency of our feature set in discriminating between classes, the performance improvement when using the feature selection method, and the high classification accuracy obtained on our real-time system on both DSP (TMS320C6415-6E3, 600 MHz) and PC (Quad Core Intel® Xeon® E5310, 2 × 4 MB Cache, 1.60 GHz, 1066 MHz) platforms.     

Automated test generation and evaluation for real-time expert systems

This paper describes a method for automated test generation and evaluation for real-time expert systems. This method supports dynamic testing, where test inputs are generated randomly within the constraints specified by a Test Specification Language. This allows the discovery of “unintended functionalities,” which may not be possible either through static testing or expert-supplied test cases. Automated test generation also allows rapid regeneration of test suites as the system evolves through various prototypes and versions. the Test Specification Language provides constructs for dealing with real-time constraints. Sample specifications and results implemented within the Activation Framework software development tool are also described. © 1994 John Wiley & Sons, Inc.     

Data communication between an expert system shell and a conventional algorithmic program with application to cam motion specification

Although more and more expert system shells have begun to provide communication interfaces to conventional procedural languages, the interfaces are basically shell- and language-dependent. This paper presents a simple, shell- and language-independent data communication technique between a shell and a procedural language via a concept analogous to the handshake data transmission used in microprocessors. A control file is used for the action of handshake. The communication interface is between two data files in two different language environments. A program written in a LISP-based expert system shell, OPS 5, and one written in a procedural language, FORTRAN, were tested to verify the presented technique.An expert system for cam motion specification, which needs the following three tasks—symbolic representation, numerical computation, and their communication—is described as one of the possible applications of the technique. These three tasks are essential to automated engineering design and analysis.     

Optimal guessing of an object by expert system

In recent decades, the development and application of expert systems has been under intensive study (e.g., see [1?C3]). The construction of an optimal algorithm for guessing an object by sequentially asking questions about its properties in the case when the answers may be incorrect is considered. This algorithm can be used in expert systems. Several optimization criteria are considered. It is concluded that the most practical criterion is the entropy minimization. The one-step entropy minimization is an analog of a deterministic greedy algorithm. The question asked by the expert system that minimizes the entropy can be chosen at each step of the procedure for any search depth depending on available computational resources.     

Computer simulation systems for development of knowledge bases of onboard online intelligent systems of system-generating core of anthropocentric object

Classification and pattern of computer simulation systems is presented; these systems provide improvement of knowledge bases of onboard intelligent systems at particular stages of their development. For intelligent information system (first global control level of anthropocentric object) “Situation awareness of the crew”, the presence of a man-operator in the simulation loop is mandatory, and for onboard online advisory expert systems for typical situations of functioning an anthropocentric object (second global level of object control), the simulation of the operator work by a special situation control block is admissible.     

Tracking control for an object in pushing operation

In this paper, we consider the problem of making a manipulator push an object on a flat floor with a point of contact to a desired position. A manipulator control method for the object to follow a planned trajectory is proposed. First, using the given distribution of frictional forces between the object and the floor, we find a particular point, named pseudo center, on which the motion of the pushed object can be approximated by the motion of a wheeled mobile robot on its center. Then, a control rule for the pushing operation is derived by applying a tracking control rule for a nonholonomic mobile robot at the pseudo center. This method makes it possible for the robot to perform the tracking control in the pushing operation. A simulation result shows the effectiveness of the proposed method. Finally, we present an approach for using a mobile manipulator to realize the pushing operation. Experimental verification of the proposed method was performed and the result is described. ©1997 John Wiley & Sons, Inc.     

Designing a practical user interface for an expert system shell

Abstract: This paper describes some of the problems encountered in developing a user interface for a commercial expert system. The emphasis is on the practical side of interface implementation while attempting to follow the many guidelines presented in the literature.     

Covert motion trajectories for an airborne object in the detection zone of an onboard Doppler radar station

We study the characteristic features of the detection zone for an onboard radar station for an early radar detection system operating in the impulse-Doppler mode. We show that due to these features, there exist covert trajectories such that objects flying along such trajectories are not detected by this onboard radar station. We derive differential equations that define covert trajectories, find various forms of covert trajectories, and study their properties.     

Investigation of the operation process of a repairable technical object in an expert servicing system with an artificial neural network

The paper presents a system for the diagnosis of repairable technical objects with the use of an artificial neural network of a radial basis function (RBF) type. The structure and the algorithm of the work of an RBF type neural network are described. This paper presents a method to control an operation process of a complex technical object with the use of trivalent diagnostic information. Also, a general diagram of the complex technical object was presented, and its internal structure was described. A diagnostic analysis was conducted, as a result of which the sets of the functional elements of the object and its diagnostic signals were determined. Also, the methodology of the diagnostic examination of the technical system was presented. The result was a functional and diagnostic model, which constituted the basis for initial diagnostic information which is provided by the sets of information concerning the elements of the basic modules and their output signals. The final results obtained for the computations conducted by the DIAG programme were presented in the table of the states of the object.     

A general criterion and an algorithmic framework for learning in multi-agent systems

We offer a new formal criterion for agent-centric learning in multi-agent systems, that is, learning that maximizes one’s rewards in the presence of other agents who might also be learning (using the same or other learning algorithms). This new criterion takes in as a parameter the class of opponents. We then provide a modular approach for achieving effective agent-centric learning; the approach consists of a number of basic algorithmic building blocks, which can be instantiated and composed differently depending on the environment setting (for example, 2- versus n-player games) as well as the target class of opponents. We then provide several specific instances of the approach: an algorithm for stationary opponents, and two algorithms for adaptive opponents with bounded memory, one algorithm for the n-player case and another optimized for the 2-player case. We prove our algorithms correct with respect to the formal criterion, and furthermore show the algorithms to be experimentally effective via comprehensive computer testing.     

Fast real-time onboard processing of hyperspectral imagery for detection and classification

Remotely sensed hyperspectral imagery has many important applications since its high-spectral resolution enables more accurate object detection and classification. To support immediate decision-making in critical circumstances, real-time onboard implementation is greatly desired. This paper investigates real-time implementation of several popular detection and classification algorithms for image data with different formats. An effective approach to speeding up real-time implementation is proposed by using a small portion of pixels in the evaluation of data statistics. An empirical rule of an appropriate percentage of pixels to be used is investigated, which results in reduced computational complexity and simplified hardware implementation. An overall system architecture is also provided.