Knowledge Representation, Reasoning and Integration Using Temporal Logic with Clocks

Representation, reasoning about and integrating knowledge based on multiple time granularities in knowledge-based systems is important, especially when talking about events that take place in the real world. Formal approaches based on temporal logics have been successfully applied in many application domains of knowledge-based systems where the evolution of a system and its environment through time is central. This paper presents a methodology based on temporal logic to deal with knowledge based on multiple time granularities in knowledge-based systems. The temporal logic we consider is especially suitable for modelling events with different rates and/or scales of progress. The methodology includes an approach to the representation of timing systems, a method used for representing facts and rules in a knowledge-based system that involve multiple time granularities using temporal logic, and several deductive reasoning techniques. The work presented in this article has been supported in part by The Australian Research Council and Macquarie University. Note that this paper is an extended and revised version of Orgun, Liu and Nayak [37].     

Automated model construction: A logic based approach

Attempts to integrate Artificial Intelligence (AI) techniques into Decision Support Systems (DSS) have received much attention in recent years. Significant among these has been the application of knowledge-based techniques to support various phases of the modeling process. This paper describes a logic based approach to mechanically construct Linear Programming (LP) models from qualitative problem specifications and illustrates it in the context of production, distribution and inventory planning problems. Specifically, we describe the features of a first-order logic based formal language called PM which is at the heart of an implemented knowledge-based tool for model construction. Problems specified in PM define a logic model which is then used to generate problem-specific inferences, and as input to a set of logic programming procedures that perform model construction.     

Soft Systems Models for Knowledge Elicitation and Representation

The paper contends that the conceptual modes used in Soft Systems Methodology have an unusual logical status. This enables them to be rendered in modal logic and used as a framework for knowledge elicitation and for the design of knowledge-based systems with learning capability.     

Knowledge-based manpower planning

The capacity performance of knowledge-based systems differs essentially from the one of traditional systems. The result is that already today these systems are employed in a number of application areas, and that the intensity of research and development in this field is very high.In this paper the development of a knowledge-based manpower planning system (KBMS) is described. The two main components of this system are a knowledge-based system developed for management planning and a model designed for manpower planning in personnel leasing companies. This model was realized as a KBMPS by applying the knowledge-based system, which was developed for management planning.     

知识型公共组织运作的相对效率研究

提出了知识型公共组织的概念，建立了知识型公共组织相对效率评价的指标体系，并着重论述了如何将测度无形知识资源的隐性主观指标与测度有形物质资源的客观指标结合，以形成对投入产出指标所含的知识总量的测度。在此基础上，运用方法对知识型公共组织进行了效率分析，并以公安组织为例，得出了提高公共组织效率的政策建议。     

Rapid fault-tolerant control prototyping for mobile robots

The main purpose of the paper is to present a fault-tolerant control system of an autonomous mobile robot. The authors present a framework for rapid prototyping of a behavior-based control system relying on tools and technologies of the Microsoft R Robotics Developer Studio. Fault detection and isolation is carried out with the help of the model-based and knowledge-based diagnostics. The first approach is developed by applying recurrent neural networks for residual generation and fuzzy logic for their evaluation. The second approach depends on scalar feature estimation and fuzzy reasoning. Basing on this information rules represented in the form of a decision table are applied for robot's behavior reconfiguration. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Introducing global constraints in CHIP

The purpose of this paper is to show how the introduction of new primitive constraints (e.g., among, diffn, cycle) over finite domains in the constraint logic programming system CHIP result in finding very rapidly good solutions for a large class of difficult sequencing, scheduling, geometrical placement and vehicle routing problems. The among constraint allows us to specify sequencing constraints in a very concise way. For the first time, the diffn constraint allows us to express and to solve directly multi-dimensional placement problems, where one has to consider nonoverlapping constraints between n-dimensional objects (e.g., rectangles, parallelepipeds). The cycle constraint makes it possible to specify a wide range of graph partitioning problems that could not yet be expressed by using current constraint logic programming languages. One of the main advantages of all these new primitives is to take into account more globally a set of elementary constraints. Finally, we point out that all the previous primitive constraints enhance the power of the CHIP system significantly, allowing us to solve real life problems that were not within reach of constraint technology before.     

An intelligent system for prioritisation of organ transplant patient waiting lists using fuzzy logic

The objective of this paper is to investigate the effectiveness of using fuzzy logic in a complex decision-making capacity, and in particular, for the prioritisation of kidney transplant recipients. Fuzzy logic is an extension to Boolean logic allowing an element to have degrees of true and false as opposed to being either 100% true or 100% false. Thus, it can account for the ‘shades of grey’ found in many real-world situations. In this paper, two fuzzy logic models are developed demonstrating its effectiveness as a model for vastly improving the current prioritisation system used in the UK and abroad. The first model converts an element of the current kidney transplant prioritisation system used in the UK into fuzzy logic. The result is an improvement to the current system and a demonstration of fuzzy logic as an effective decision-making approach. The second model offers an alternative prioritisation system to overcome the limitations of the current system both in the UK and abroad, as brought up by research reviewed in this paper. The current UK transplant prioritisation system, adapted in the first model, uses objective criteria (age of recipient, waiting time, etc) as inputs into the decision-making process. This alternative model takes advantage of the facility for infinitely varying inputs into fuzzy logic and a system is developed that can handle subjective (humanistic) criteria (pain level, quality of life, etc) that are key to arriving at such important decisions. Furthermore, the model is highly flexible allowing any number of criteria to be used and the individual characteristics of each criterion to be altered. The result is a model that utilises the scope of fuzzy logic's flexibility, usability and effectiveness in the field of decision-making and a transplant prioritisation method vastly superior to the original system, which is constrained by its use of only objective criteria. The ‘humanistic’ model demonstrates the ability of fuzzy logic to consider subjective and complex criteria. However, the criteria used are not intended to be exhaustive. It is simply a template to which medical professionals can apply limitless additional criteria. The model is produced as an alternative to any current national system. However, the model can also be used by individual hospitals to decide initially whether a patient should be placed on the transplant or surgery waiting list. The model can be further adapted and used for the transplant of other organs or similar decisions in medicine. Concurrently with the research and work carried out to develop the two models the investigation focused on the constraints of the current systems used in the UK and the US and the seemingly impossible dilemmas experienced by those having to make the prioritisation decisions. By removing the parameters of objective-only inputs the ‘humanistic’ model eradicates the previous limitations on decision-making.     

Comparing proposals for the solution of data analysis problems in a knowledge-based system

In a knowledge-based system, which aims at supporting persons who are interested in the analysis of special data, the problem can arise that a whole set of proposals is generated in answer to a question of a user. Such proposals are based on appropriate interconnections between user wishes, available original data as well as derived data obtained by application of adequate methods, the methods mentioned, and data analysis objectives. We use graphical visualizations of proposals to outline how the system would cope with the underlying situation.In this paper, special attention is paid to the concept of knowledge-based comparisons of proposals when propagation of certainty factors is used for a-priori judgments of proposals generated (before suggested proposals are performed). After-wards, a-posteriori judgments of proposals considered (after solutions have been computed by application of selected proposals) can be based on goodness of fit criteria derived from chosen outputs.     

Translating statements of symbolic logic into zero-one linear programming

Symbolic logic can be used to translate verbal statements of the optimization problem into an exact mathematical form. There are then three stages in the problem formulation—the verbal stage, the logical stage and the mathematical stage. The purpose of this paper is to translate statements of symbolic logic into the language of zero-one linear programming. Concepts of symbolic logic and zero-one linear programming will be described with examples of translating verbal statements into symbolic logic, and of translating logical statements into a mathematically equivalent form.     

A Knowledge-based Approach to Production Planning

This paper discusses a knowledge-based approach to production planning, the process of establishing production rates, work force levels and on-hand inventories for product families as a possible alternative to traditional operational research methods. It describes one company's experienced-based approach to production planning and how this was incorporated into a knowledge-based system. The production planning state-space, use of common planning constraints and heuristic procedures, and a prototype of a knowledge-based system that develops production plans for one product family are also described.     

Mixed logic and storage operators

In 1990 J-L. Krivine introduced the notion of storage operators. They are -terms which simulate call-by-value in the call-by-name strategy and they can be used in order to modelize assignment instructions. J-L. Krivine has shown that there is a very simple second order type in AF2 type system for storage operators using G?del translation of classical to intuitionistic logic. In order to modelize the control operators, J-L. Krivine has extended the system AF2 to the classical logic. In his system the property of the unicity of integers representation is lost, but he has shown that storage operators typable in the system AF2 can be used to find the values of classical integers. In this paper, we present a new classical type system based on a logical system called mixed logic. We prove that in this system we can characterize, by types, the storage operators and the control operators. Received: 7 May 1997     

Optimization of the MHH stellarator

The Modular Helias-like Heliac is a coil configuration selected two years ago for the U.S. Stellarator Power Plant Study. Since that time the design has been significantly improved by running a collection of three-dimensional plasma physics codes. An attractive choice seems to be three field periods, aspect ratio six for the plasma, and rotational transform ranging from 1/4 at the magnetic axis down to 1/5 at the separatrix. The torsion of the modular coils is low, and they are spaced well apart from each other and from the plasma. © 1997 John Wiley & Sons, Inc.     

Funnel control for fully actuated systems under a fragment of signal temporal logic specifications

Temporal logics have lately proven to be a valuable tool for various control applications by providing a rich specification language. Existing temporal logic-based control strategies discretize the underlying dynamical system in space and/or time. We will not use such an abstraction and consider continuous-time systems under a fragment of signal temporal logic specifications by using the associated robust semantics. In particular, this paper provides computationally-efficient funnel-based feedback control laws for a class of systems that are, in a sense, feedback equivalent to single integrator systems, but where the dynamics are partially unknown for the control design so that some degree of robustness is obtained. We first leverage the transient properties of a funnel-based feedback control strategy to maximize the robust semantics of some atomic temporal logic formulas. We then guarantee the satisfaction for specifications consisting of conjunctions of such atomic temporal logic formulas with overlapping time intervals by a suitable switched control system. The result is a framework that satisfies temporal logic specifications with a user-defined robustness when the specification is satisfiable. When the specification is not satisfiable, a least violating solution can be found. The theoretical findings are demonstrated in simulations of the nonlinear Lotka–Volterra equations for predator–prey models.     

Hybrid modeling approach for vehicle frame coupled with nonlinear dampers

The vehicle frame system comprises frame structure and nonlinear dampers. In order to investigate the effects of frame flexibility and nonlinear hysteresis, a hybrid modeling approach for vehicle frame coupled with nonlinear dampers will be proposed. Before that, a complex model for nonlinear damper is developed consisting of knowledge-based model and support vector machine (SVM) model. The frame structure is modeled by FEM where the SVM complex model of damper is embedded in. Thus a hybrid model for vehicle frame system is established and successfully validated via a dummy vehicle riding in different conditions. The results show that the hybrid model can capture the nonlinear dynamic characteristics accurately. The hybrid model can also provide a basis for structural design with the existing of FEM model.     

Symbolic integration of logic in MILP branch and bound methods for the synthesis of process networks

This paper deals with the branch and bound solution of process synthesis problems that are modelled as mixed-integer linear programming (MILP) problems. The symbolic integration of logic relations between potential units in a process network is proposed in the LP based branch and bound method to expedite the search for the optimal solution. The objective of this integration is to reduce the number of nodes that must be enumerated by using the logic to decide on the branching of variables and to determine by symbolic inference whether additional variables can be fixed at each node. The important feature of this approach is that it does not require additional constraints in the MILP and the logic can be systematically generated for process networks. Strategies for performing the integration are proposed that use the disjunctive and conjunctive normal form representations of the logic, respectively. Computational results will be presented to illustrate that substantial savings can be achieved.     

Ternary Operations as Primitive Notions for Constructive Plane Geometry V

In this paper we provide a quantifier-free, constructive axiomatization of metric-Euclidean and of rectangular planes (generalizations of Euclidean planes). The languages in which the axiom systems are expressed contain three individual constants and two ternary operations. We also provide an axiom system in algorithmic logic for finite Euclidean planes, and for several minimal metric-Euclidean planes. The axiom systems proposed will be used in a sequel to this paper to provide ‘the simplest possible’ axiom systems for several fragments of plane Euclidean geometry. Mathematics Subject Classification: 51M05, 51M15, 03F65.     

一类模糊逻辑系统幺半群与同态映射

首先利用代数中幺半群的概念给出了模糊逻辑系统专业领域的概念, 建立专业领域概念的目的是为了规范模糊逻辑系统中语言变量的取值范围, 从而将模糊逻辑系统看作是某个笛卡儿乘积幺半群的有限子集. 然后利用这个笛卡儿乘积幺半群的乘积运算构造了模糊逻辑系统幺半群. 最后, 在一定的约定条件下证明了通常使用的一类Mamdani形模糊逻辑系统的输出可以看作是从模糊逻辑系统幺半群到连续函数域的同态映射.     

Generalized resolution and cutting planes

This paper illustrates how the application of integer programming to logic can reveal parallels between logic and mathematics and lead to new algorithms for inference in knowledge-based systems. If logical clauses (stating that at least one of a set of literals is true) are written as inequalities, then the resolvent of two clauses corresponds to a certain cutting plane in integer programming. By properly enlarging the class of cutting planes to cover clauses that state that at least a specified number of literals are true, we obtain a generalization of resolution that involves both cancellation-type and circulant-type sums. We show its completeness by proving that it generates all prime implications, generalizing an early result by Quine. This leads to a cutting-plane algorithm as well as a generalized resolution algorithm for checking whether a set of propositions, perhaps representing a knowledge base, logically implies a given proposition. The paper is intended to be readable by persons with either an operations research or an artificial intelligence background.This report was prepared as part of the activities of the Management Sciences Research Group, Carnegie-Mellon University. Reproduction in whole or in part is permitted for any purpose of the U.S. Government.