Formal semantics of meta‐level architectures: Dynamic control of reasoning

Meta‐level architectures for dynamic control of reasoning processes are quite powerful. In the literature, many applications in reasoning systems modeling complex tasks are described, usually in a procedural manner. In this article we present a semantic framework based on temporal partial logic to describe the dynamics of reasoning behavior. Using these models, the semantics of the behavior of the whole (meta‐level) reasoning system can be described by a set of (intended) temporal models. © 2002 Wiley Periodicals, Inc.     

Lyapunov based reasoning methods

Semiquantitative simulation is an approach for the analysis of uncertain dynamic systems that performs a comprehensive simulation study based on automated reasoning methods. Semiquantitative simulation of complex models is, however, hindered by the limited automated reasoning capabilities of the currently available semiquantitative simulation techniques. The paper describes the extension of semiquantitative simulation techniques on the basis of Lyapunov methods. This extension improves automated reasoning by utilizing generalized energy functions, called Lyapunov functions. Automated reasoning based on Lyapunov functions can be seen as a generalization of the energy considerations employed by engineers. It has the advantage that it can be used to analyze systems where it does not make sense to speak about energy in the physical sense. The difficult task of deducing a Lyapunov function for the semiquantitatively modeled dynamic system is solved by reformulating methods from nonlinear control theory. A procedure for an automatic deduction of a Lyapunov function and Lyapunov-based reasoning methods using this deduced Lyapunov function are given. The improved automated reasoning capabilities of our extended SQSIM simulation platform are demonstrated by example     

An adaptive Student Centered Curriculum for an intelligent training system

An intelligent tutoring system customizes its presentation of knowledge to the individual needs of each student based on a model of the student. Student models are more complex than other user models because the student is likely to have misconceptions. We have addressed several difficult issues in reasoning about a student's knowledge and skills within a real-time simulation-based training system. Our conceptual framework enables important aspects of the tutor's reasoning to be based upon simple, comprehensible representations that are the basis for a Student Centered Curriculum. We have built a system for teaching cardiac resuscitation techniques in which the decisions abouthow to teach are separated from the decisions aboutwhat to teach. The training context (i.e., choice of topics) is changed based on a tight interaction between student modeling techniques and simulation management. Although complex student models are still required to support detailed reasoning about how to teach, we argue that the decision about what to teach can be adequately supported by qualitatively simpler techniques, such as overlay models. This system was evaluated in formative studies involving medical school faculty and students. Construction of the student model involves monitoring student actions during a simulation and evaluating these actions in comparison with an expert model encoded as a multi-agent plan. The plan recognition techniques used in this system are novel and allow the expert knowledge to be expressed in a form that is natural for domain experts.     

面向对象编程与定理证明相结合实现问题自动求解

本文针对一类智能决策支持系统中,基于模型行为仿真以实现解题过程自动化的需要,提出对模型对象行为的一阶谓词演算型表达和面向对象型模型处理过程的形式化体系。将问题自动求解过程转化为逻辑运算过程,通过归结反演求取问题的解。文中给出一个应用实例。     

STRUCTURED REPRESENTATION OF FMS INTEGRATING SI-NETS AND HIGH LEVEL PETRI NETS

In this paper a structured knowledge-based approach to the representation and scheduling of flexible manufactoring systems (FMSs) is described. Our approach is based on a structured conceptual representation (a KL-ONE-like Si-net representation formalism), extended with an instant-based temporal reasoning formalism. Furthermore, the approach integrates a particular extension to high-level Petri nets (PNs), structured timed colored Petri nets (STCPNs), for the modeling and simulation of the FMS. Such a representation scheme allows us to use SI-nets' good properties related to inference (classification and inheritance), which are lacking in PNs, and at the same time provides an extension toward an explicit representation for time. The integration of Si-nets with PNs is necessary because simulation and low-level coordination of FMSs require a procedural approach that is not within the aims of Si-nets. Therefore, procedural and symbolic levels, corresponding to the different hierarchical levels of the representation and control system of the FMS, coexist in the system. Using a qualitative terminology, we may also call them analog and symbolic knowledge. We assume that such a hybrid representation system may be useful, since a procedural representation, integrated within a logic formalism, can increase the expressive power without complicating the notation or the representation itself. The paper describes both the representational aspects and the modeling of the control system of the FMS, focusing on the interaction mechanisms among the different levels of representation. In particular, we show how an STCPN-based model can be automatically derived starting from the symbolic component of the system. A particular FMS case study, regarding a class of problems of resource-constrained multiproject scheduling (where projects are sets of tasks temporally related), is discussed.     

基于G2的电子战仿真技术研究

现代电子战(EW)作战系统规模日趋庞大,作战环境也日趋复杂,对用计算机进行EW仿真提出了更高要求.如何将面向对象建模、人工智能等技术应用到EW仿真中是当前研究的重点之一.文中运用面向对象建模方法建立EW作战系统的实体模型和行为模型,并与描述EW电磁环境的数学模型一起构成仿真模型库.然后以仿真模型库为基础,利用智能系统平台的知识表达和实时推理能力,建立了仿真规则知识库并以专家系统产生式推理的方式实现规则驱动的仿真运行.这种基于面向对象、知识推理的仿真已应用于EW作战系统的效能评估,并为战法研究、策略评估等更高层次的EW仿真提供了有力的手段.     

Intelligent on-line system identification using a blackboard system

Adaptive control systems have been developed and used for a number of decades. However, there are still some problems with their operation, which limit wider industrial adoption. This paper addresses one aspect of adaptive control, namely the on-line system identification of the time-varying process being controlled. The approach adopted is to use a blackboard system to identify the time-varying process model. The blackboard system contains knowledge sources with, algorithmic, fuzzy-logic and evolutionary reasoning. The paper describes the design of a computer simulation of this approach, concentrating on the fuzzy reasoning used to validate the multiple models, and the evolutionary techniques used to reject poor models and introduce better models. The computer simulation is then evaluated, firstly using simulated plant data and then using real plant data from an experimental hot air dryer. It is concluded that the technique is practical, and worthy of further testing on a pilot plant.     

基于格值一阶逻辑LF（X）的自动推理算法

基于谓词逻辑的归结推理方法是目前理论上较为成熟、可以在计算机上实现的推理方法之一。针对格值一阶逻辑LF(X)中归结自动推理问题,以格值一阶逻辑LF(X)的α-归结原理为理论基础,通过对例子进行分析,提出了LF(X)中简单广义子句集的归结自动推理算法,并证明了该算法的可靠性和完备性。     

QUBICS: A general quantity base management system

The problem of ambiguities has presented an obstacle to the practical use of qualitative simulation in dealing with real-life dynamic systems. One of the dominant causes of these prevailing ambiguities is the parsimonious use of information by current qualitative simulation models. Humans seem to utilize more quantity information to produce less ambiguous predictions when reasoning on dynamic mechanisms. To cover such human algebraic reasoning, the representation and processing of quantity information should be extended. This paper presents an inference system specialized for processing quantity information in order to support qualitative simulation. The system stores the information in the form of constraints into a quantity base, a notion that is parallel to the symbolic fact base, and processes queries based on linear programming techniques and goal-tree search. Temporal reasoning is also facilitated through an improved utilization of derivative information.     

A method to exchange procedurally represented 2D CAD model data using ISO 10303 STEP

Procedural models have the advantage of being easy to edit simply by changing the values of the parameters of their constructional operations. Such models are said to embody design intent, in the sense that modifications to them conform to the method of creation used by their original creator. They also comply with any constraints implied by the particular constructional operations used. This paper introduces the development and standardization process of the ISO 10303-112 specification and describes the concept of procedural 2D modeling, a method of representing procedural 2D CAD models in STEP in harmony with other STEP resources. The feasibility of procedural 2D modeling commands for the exchange of procedurally represented 2D CAD model data is demonstrated through an experiment where procedural 2D CAD model data in neutral form generated with an in-house 2D modeling system are translated to and modified in a commercial 3D mechanical CAD system.     

一种飞行器任务评估系统的设计与实现

针对火箭等飞行器在试飞任务过程中,测量种类众多且关系复杂的问题,提出了一种两阶段评估飞行任务的技术方案.该方案根据不同数据的处理方式,将评估过程分为证据获取阶段和评估推理阶段.在证据获取阶段,采用分布式获取数据的技术,将遥测、轨道等数据和图像数据分开,采用不同的模型并行获取证据.在评估推理阶段,采用专家系统模型,汇集各种证据(遥测、轨道、图像等)进行综合推理,得出评估结论.仿真表明,该系统可以满足即时评估的需求.     

基于个性和OCC的机器人情感建模研究

机器人不仅要具有简单的机械作业和逻辑推理能力，还应当具有类似人类的情感能力．本文将个性与情绪、情感、理解、表达相结合，采用OCC模型作为评价标准，建立了符合人类情感规律的、可用于情感机器人的情感模型。通过一个应用上述模型的虚拟人情感交互系统．验证了此模型可以很好的对人类的情感进行仿真．可以应用于情感机器人和人性化计算机、游戏等许多领域。     

The completeness of functional logic

A new first-order logic, functional logic, was proposed recently by Staples, Robinson and Hazel. The logic provides a formal means of describing and reasoning about dependence on an implicit parameter, a prime motivation being the unification of the Hoare logic used to reason about procedural programs with the powerful and well established techniques of classical logic. Viewed more abstractly, independently of possible applications, functional logic may be described as a logic with primitives, axioms and inference rules appropriate for reasoning about the properties of mathematical functions. In this paper, the completeness of functional logic is proved; that is, it is shown that any term of a theory in the logic which is true in all models is a theorem.This work was done while the author was a visitor to the Key Centre for Software Technology, Department of Computer Science, The University of Queensland, Queensland 4072, Australia.     

Automatic case acquisition from texts for process-oriented case-based reasoning

This paper introduces a method for the automatic acquisition of a rich case representation from free text for process-oriented case-based reasoning. Case engineering is among the most complicated and costly tasks in implementing a case-based reasoning system. This is especially so for process-oriented case-based reasoning, where more expressive case representations are generally used and, in our opinion, actually required for satisfactory case adaptation. In this context, the ability to acquire cases automatically from procedural texts is a major step forward in order to reason on processes. We therefore detail a methodology that makes case acquisition from processes described as free text possible, with special attention given to assembly instruction texts. This methodology extends the techniques we used to extract actions from cooking recipes. We argue that techniques taken from natural language processing are required for this task, and that they give satisfactory results. An evaluation based on our implemented prototype extracting workflows from recipe texts is provided.     

Efficient parallel reasoning on fuzzy goal models for run time requirements verification

As software applications become highly interconnected in dynamically provisioned platforms, they form the so-called systems-of-systems. Therefore, a key issue that arises in such environments is whether specific requirements are violated, when these applications interact in new unforeseen ways as new resources or system components are dynamically provisioned. Such environments require the continuous use of frameworks for assessing compliance against specific mission critical system requirements. Such frameworks should be able to (a) handle large requirements models, (b) assess system compliance repeatedly and frequently using events from possibly high velocity and high frequency data streams, and (c) use models that can reflect the vagueness that inherently exists in big data event collection and in modeling dependencies between components of complex and dynamically re-configured systems. In this paper, we introduce a framework for run time reasoning over medium and large-scale fuzzy goal models, and we propose a process which allows for the parallel evaluation of such models. The approach has been evaluated for time and space performance on large goal models, exhibiting that in a simulation environment, the parallel reasoning process offers significant performance improvement over a sequential one.     

定性仿真和功能推理在系统故障诊断中应用

针对电路系统的特点,提出一种基于定性仿真和功能推理的故障诊断方法。在对电路系统进行简化与拆分的基础上,建立元件的定性仿真模型,对拆分后的电路系统进行定性仿真和推理,确定系统中功能执行元件的工作状态,并与实际的电路进行比较,从而将故障进行隔离定位。仿真实例说明了该方法的有效性。