A logic-based mechanical system constraint model

This paper: (1) classifies design constraints of mechanical systems from a multi-disciplinary, concurrent engineering point of view from three orthogonal bases: application, object, and expression, (2) presents some initial developments in extending data models to include design constraints, formally defining entity relationships using first order predicate logic, and modeling assembly related geometry constraints for mechanical systems using predicates. Axioms and atomic formulas of mechanical assemblies are developed. Two frequently used assembly relationships-fit and against—are defined and used to explain the assembly definition axiom of a piston assembly of an engine model. Such a geometry constraint modeling method builds a basis for design change propagation and change management.     

L-CATA: A logic-based expert travel system

L-CATA (Logic-based Computer Aided Travel Assistant) is a logic-based expert database system, which asks the user to input his query specification, such as starting place, destination, constraints, rules and goals, etc., and outputs a list of flights meeting the traveller's specification; together with an alternative list which may not quite meet the user's specification but optimizes his goals. L-CATA is written as a deductive database system, and uses heuristic rules to prune its search of the database. Unlike other air-travel related expert systems, L-CATA does not attempt to model the traveller. Instead, L-CATA complements existing Computer Reservation Systems by providing comprehensive individually tailored advice and information to the traveller. There are several approaches to implement such a system. The logic approach is a very promising one, and the aims of L-CATA can be more easily achieved by using it. In this paper, we present a logic approach to the L-CATA expert database system, and provide a theoretical foundation for such a database system.     

Fuzzy logic-based induction motor protection system

The protection is very important to detect abnormal motor running conditions such as over current, over voltage, overload, over temperature, and so on. When a failure is sensed by the protection system, a time delay should be specified to trip the motor. In the classical systems, motors are stopped with the time delay, which is adjusted constantly without considering the fault level. This paper presents a fuzzy logic-based protection system covering six different fault parameters for induction motors. This paper focuses on a new time-delay calculation for stopping induction motor and improves the overall detection performance. The time delay is computed by fuzzy logic method according to various fault parameters when one of the failures occurs on the motor. This system is successfully tested in real-time faults on the motor, and it shows that it provides sensitive protection by fuzzy rules.     

A hybrid,decidable, logic-based knowledge representation system1

The major problem with using standard first-order logic as a basis for knowledge representation systems is its undecidability. A variant of first-order tautological entailment, a simple version of relevance logic, has been developed that has decidable inference and thus overcomes this problem. However, this logic is too weak for knowledge representation and must be strengthened. One way to strengthen the logic is to create a hybrid logic by adding a terminological reasoner. This must be done with care to retain the decidability of the logic as well as its reasonable semantics. The result, a stronger decidable logic, is used in the design of a hybrid, decidable, logic-based knowledge representation system.     

A logic-based calculus of events

We outline an approach for reasoning about events and time within a logic programming framework. The notion of event is taken to be more primitive than that of time and both are represented explicitly by means of Horn clauses augmented with negation by failure. The main intended applications are the updating of databases and narrative understanding. In contrast with conventional databases which assume that updates are made in the same order as the corresponding events occur in the real world, the explicit treatment of events allows us to deal with updates which provide new information about the past. Default reasoning on the basis of incomplete information is obtained as a consequence of using negation by failure. Default conclusions are automatically withdrawn if the addition of new information renders them inconsistent. Because events are differentiated from times, we can represent events with unknown times, as well as events which are partially ordered and concurrent.     

A logic-based axiomatic model of bargaining

This paper introduces an axiomatic model for bargaining analysis. We describe a bargaining situation in propositional logic and represent bargainers' preferences in total pre-orders. Based on the concept of minimal simultaneous concessions, we propose a solution to n-person bargaining problems and prove that the solution is uniquely characterized by five logical axioms: Consistency, Comprehensiveness, Collective rationality, Disagreement, and Contraction independence. This framework provides a naive solution to multi-person, multi-issue bargaining problems in discrete domains. Although the solution is purely qualitative, it can also be applied to continuous bargaining problems through a procedure of discretization, in which case the solution coincides with the Kalai–Smorodinsky solution.     

A fuzzy logic-based computational recognition-primed decision model

The recognition-primed decision (RPD) model is a primary naturalistic decision-making approach which seeks to explicitly recognize how human decision makers handle complex tasks and environment based on their experience. Motivated by the need for quantitative computer modeling and simulation of human decision processes in various application domains, including medicine, we have developed a general-purpose computational fuzzy RPD model that utilizes fuzzy sets, fuzzy rules, and fuzzy reasoning to represent, interpret, and compute imprecise and subjective information in every aspect of the model. Experiences acquired by solicitation with experts are stored in experience knowledge bases. New local and global similarity measures have been developed to identify the experience that is most applicable to the current situation in a specific decision-making context. Furthermore, an action evaluation strategy has been developed to select the workable course of action. The proposed fuzzy RPD model has been preliminarily validated by using it to calculate the extent of causality between a drug (Cisapride, withdrawn by the FDA from the market in 2000) and some of its adverse effects for 100 hypothetical patients. The simulated patients were created based on the profiles of over 1000 actual patients treated with the drug at our medical center before its withdrawal. The model validity was demonstrated by comparing the decisions made by the proposed model and those by two independent internists. The levels of agreement were established by the weighted Kappa statistic and the results suggested good to excellent agreement.     

A logic-based approach to program flow analysis

A formalism is presented for tracking assertions which hold universally, i.e., at the end of all the execution paths to a given program point, and assertions which hold existentially, i.e., at the end of some execution paths. In the formalism, the assertions which hold at a given execution path are uniformly defined by an entry environment which contains the assertions which hold when the execution of the program begins and an environment transformer for every program construct. The novel aspect of our formalism is that Horn clauses are used to specify the consistent environments and the meaning of program constructs. The best iterative algorithm (a notion defined by P. Cousot and R. Cousot) for tracking universal and existential assertions simultaneously is given. Conditions are presented under which the best iterative algorithm can be efficiently implemented. The formalism is applied to the pointer equality problem in Pascal. It is shown that universal pointer equalities may be used to reduce the number of superfluous existential equalities, and that existential equalities may be used to obtain more universal equalities. Recent empirical results indicate that tracking the combination of may and must equalities leads to substantial improvements in the result of the analysis. For programs without recursively defined records, the best iterative algorithm can be effectively implemented. These results apply to multiple levels of pointers and can be extended to handle possibly recursive procedures. However, for programs with recursively defined data types further approximations are necessary, e.g., by using a finite graph to model all the possible pointer equalities. For simplicity, this paper does not present an analysis algorithm for this case. Received: 2 September 1991 / 25 June 1997     

Fuzzy logic-based pre-classifier for tropical wood species recognition system

Classifying tropical wood species poses a considerable economic challenge and failure to classify the wood species accurately can have significant effects on timber industries. The problem of wood recognition is compounded with the nonlinearities of the features among the similar wood species. Besides that, large wood databases presented a problem of large processing time especially for online wood recognition system. In view of these problems, we propose the use of fuzzy logic-based pre-classifier as a means of treating uncertainty to improve the classification accuracy of tropical wood recognition system. The pre-classifier serve as a clustering mechanism for the large database simplifying the classification process making it more efficient. The use of the fuzzy logic-based pre-classifier has managed to increase the accuracy of the wood recognition system by 4 % and reduce the processing time for training and testing by more than 75 % and 26 % respectively.     

A logic-based approach to reverse engineering tools production

Difficulties arising in the use of documents produced by reverse engineering tools are analyzed. With reference to intermodular data flow analysis for Pascal software systems, an interactive and evolutionary tool is proposed. The tool is based on the production of intermodular data flow information by static analysis of code, its representation in a Prolog program dictionary, and a Prolog abstractor that allows the specific queries to be answered     

A logic-based integration of active and deductive databases

A logic-based approach to the specification of active database functionality is presented which not only endows active databases with a well-defined and well-understood formal semantics, but also tightly integrates them with deductive databases. The problem of endowing deductive databases with rule-based active behaviour has been addressed in different ways. Typical approaches include accounting for active behaviour by extending the operational semantics of deductive databases, or, conversely, accounting for deductive capabilities by constraining the operational semantics of active databases. The main contribution of the paper is an alternative approach in which a class of active databases is defined whose operational semantics is naturally integrated with the operational semantics of deductive databases without either of them strictly subsuming the other. The approach is demonstrated via the formalization of the syntax and semantics of an active-rule language that can be smoothly incorporated into existing deductive databases, due to the fact that the standard formalization of deductive databases is reused, rather than altered or extended. One distinctive feature of the paper is its use of ahistory, as defined in the Kowalski-Sergot event-calculus, to define event occurrences, database states and actions on these. This has proved to be a suitable foundation for a comprehensive logical account of the concept set underpinning active databases. The paper thus contributes a logical perspective to the ongoing task of developing a formal theory of active databases. Alvaro Adolfo Antunes Fernandes, Ph.D.: He received a B.Sc. in Economics (Rio de Janeiro, 1984), an M.Sc. in Knowledge-Based Systems (Edinburgh, 1990) and a Ph.D. in Computer Science (Heriot-Watt, 1995). He worked as a Research Associate at Heriot-Watt University from December 1990 until December 1995. In January 1996 he joined the Department of Mathematical and Computing Sciences at Goldsmiths College, University of London, as a Lecturer. His current research interests include advanced data- and knowledge-base technology, logic programming, and software engineering. M. Howard Williams, Ph.D., D.Sc.: He obtained his Ph.D. in ionospheric physics and recently a D.Sc. in Computer Science. He was appointed as the first lecturer in Computer Science at Rhodes University in 1970. During the following decade he rose to Professor of Computer Science and in 1980 was appointed as Professor of Computer Science at Heriot-Watt University. From 1980 to 1988 he served as Head of Department and then as director of research until 1992. He is now head of the Database Research Group at Heriot-Watt University. His current research interests include active databases, deductive objectoriented databases, spatial databases, parallel databases and telemedicine. Norman W. Paton, Ph.D.: He received a B.Sc. in Computing Science from the University of Aberdeen in 1986. From 1986 to 1989 he worked as a Research Assistant at the University of Aberdeen, receiving a Ph. D. in 1989. From 1989 to 1995 he was a Lecturer in Computer Science at Heriot-Watt University. Since July 1995, he has been a Senior Lecturer in Department of Computer Science at the University of Manchester. His current research interests include active databases, deductive object-oriented databases, spatial databases and database interfaces.     

A logic-based agent that plans for extended reachability goals

Planning to reach a goal is an essential capability for rational agents. In general, a goal specifies a condition to be achieved at the end of the plan execution. In this article, we introduce nondeterministic planning for extended reachability goals (i.e., goals that also specify a condition to be preserved during the plan execution). We show that, when this kind of goal is considered, the temporal logic ctl turns out to be inadequate to formalize plan synthesis and plan validation algorithms. This is mainly due to the fact that the ctl’s semantics cannot discern among the various actions that produce state transitions. To overcome this limitation, we propose a new temporal logic called α-ctl. Then, based on this new logic, we implement a planner capable of synthesizing reliable plans for extended reachability goals, as a side effect of model checking.     

A transformation system for concurrent processes

Program transformation techniques have been extensively studied in the framework of functional and logic languages, where they were applied mainly to obtain more efficient and readable programs. All these works are based on the Unfold/Fold program transformation method developed by Burstall and Darlington in the context of their recursive equational language. The use of Unfold/Fold based transformations for concurrent languages is a relevant issue that has not yet received an adequate attention. In this paper we define a transformation methodology for CCS. We give a set of general rules which are a specialization of classical program transformation rules, such as Fold and Unfold. Moreover, we define the general form of other rules, “oriented” to the goal of a transformation strategy, and we give conditions for the correctness of these rules. We prove that a strategy using the general rules and a set of goal oriented rules is sound, i.e. it transforms CCS programs into equivalent ones. We show an example of application of our method. We define a strategy to transform, if possible, a full CCS program into an equivalent program whose semantics is a finite transition system. We show that, by means of our methodology, we are able to a find finite representations for a class of CCS programs which is larger than the ones handled by the other existing methods. Our transformational approach can be seen as unifying in a common framework a set of different techniques of program analysis. A further advantage of our approach is that it is based only on syntactic transformations, thus it does not requires any semantic information. Received: 24 April 1997 / 19 November 1997     

Non-determinism in logic-based languages

The use of non-determinism in logic-based languages is motivated using pragmatic and theoretical considerations. Non-deterministic database queries and updates occur naturally, and there exist non-deterministic implementations of various languages. It is shown that non-determinism resolves some difficulties concerning the expressive power of deterministic languages: there are non-deterministic languages expressing low complexity classes of queries/updates, whereas no such deterministic languages are known. Various mechanisms yielding non-determinism are reviewed. The focus is on two closely related families of non-deterministic languages. The first consists of extensions of Datalog with negations in bodies and/or heads of rules, with non-deterministic fixpoint semantics. The second consists of non-deterministic extensions of first-order logic and fixpoint logics, using thewitness operator. The expressive power of the languages is characterized. In particular, languages expressing exactly the (deterministic and non-deterministic) queries/updates computable in polynomial time are exhibited, whereas it is conjectured that no analogous deterministic language exists. The connection between non-deterministic languages and determinism is also explored. Several problems of practical interest are examined, such as checking (statically or dynamically) if a given program is deterministic, detecting coincidence of deterministic and non-deterministic semantics, and verifying termination for non-deterministic programs.Work supported by the Projet de Recherche Coordonnée BD3.Work supported in part by the National Science Foundation under grants IRI-8816078 and INT-8817874. The work was done in part while the author was visiting INRIA.     

Hoare logic-based genetic programming

Almost all existing genetic programming systems deal with fitness evaluation solely by testing. In this paper, by contrast, we present an original approach that combines genetic programming with Hoare logic with the aid of model checking and finite state automata, henceby proposing a brand new verification-focused formal genetic programming system that makes it possible to evolve reliable programs with mathematically-verified properties.     

A fuzzy logic-based predictor for predictive coding of images

In this paper, we present a fuzzy logic-based nonlinear predictor for predictive coding of images. We define five local structure patterns of images: uniform area, horizontal contour (0°), vertical contour (90°), 45°, and 135° diagonal contours. Their membership functions are derived with the gradient-based edge detection method and predicted values for different patterns are defined by linear extrapolation from available neighborhood pixel values. The predicted value of the current pixel can be obtained based on the membership functions and the defined predicted values for the different patterns. A set of parameters to characterize the proposed fuzzy predictor are determined from empirical data. Success in the use of the proposed predictor is demonstrated, by using simulation results through the reduction in the entropy as compared to those of existing linear and nonlinear ones. It is also shown that the proposed fuzzy predictor can be efficiently implemented