基于CLIPS的油水井动态分析模型研究与实现

针对当前油田油水井动态分析流程复杂、计算量大并依赖于经验丰富的专家等问题,提出一种基于CLIPS专家系统外壳的油水井动态分析模型。获取油水井动态分析经验知识并对其分类总结,研究知识的表示、存储、管理技术以及将知识编译成符合CLIPS语法形式的方法,设计数据-事实解释机制实现从油田生产数据库自动抽取推理事实,利用CLIPS内核进行推理并对结果进行解释。最后将油水井动态分析模型应用在油田实际项目中,证明了该模型的可行性和有效性。     

CLIPS与高级语言交互的研究与实现

CLIPS(C Language Integrated Production System)是一种专家系统开发语言,它支持3种程序设计方式:基于规则的、面向对象的和过程性的。文中介绍了CLIPS与其他高级语言间的交互。讨论了CLIPS如何调用外部程序,如何将CLIPS嵌入到其他高级语言中。并举例说明了该交互实现的具体过程。最后介绍了用CLIPS构建的专家系统。     

不确定时态信息表示的统一模型

时态信息表示和推理是人工智能研究中的一个重要课题,现有的模型大多只能表示确定时态信息,然而现实生活中很多事件的发生结束等时态信息都是不确定的。故提出了一个表示不确定时态信息的统一模型,可用于描述各种具有确定或不确定时态信息的事件。该模型首先定义各类时态对象(如时间点、时间区间)以及它们之间的关系,并给出时态对象间的传递关系表,利用该表能进行时态一致性约束满足问题的求解。最后,给出了两个不确定时态推理的例子,表明了该模型的实际应用意义。     

Scenario-based knowledge representation in case-based reasoning systems

A scenario-based representation model for cases in the domain of managerial decision-making is proposed. The scenarios in narrative texts are converted to scenario units of knowledge organization. The elements and structure of the scenario unit are defined. The scenario units can be linked together or coupled with others. Compared with traditional case representation methods based on database tables or frames, the proposed model is able to represent knowledge in the domain of managerial decision-making at a much deeper level and provide much more support for case-based systems employed in business decision-making.     

带测试动作的动态时序逻辑扩展

作为一种动态知识表示形式,动态时序逻辑(DLTL)尤适用于正规程序验证,然而它不直接支持测试动作,这使得其应用受到一定限制。为支持测试动作,提出一个DLTL扩展DLTL+和一个判定DLTL+公式可满足性的tableau算法,并给出了算法的正确性以及其时间复杂度为2O(n)的证明。分析表明,DLTL+提供了一种直接的、有效的测试动作支持方式,该方式比已知的其他方式更具有实际应用价值。     

Time representation: A taxonomy of temporal models

The objective of the paper is to provide a taxonomy of temporal systems according to three fundamental considerations: the assumed axiomatic theory, the expressiveness, and the mechanisms for inference which are provided. There is an discussion of the significance of the key features of the taxonomy for computer modelling of temporal events. A review considers the most significant representative systems with respect to these issues, including those due to Bruce, Allen and Hayes, Vilain, McDermott, Dechteret al., Kahn and Gorry, Kowalski and Sergot, Bacchuset al., and Knight and Ma. A tabular comparison of systems is given according to their main structural features. In conclusion, the characteristics of a general axiomatic system capable of representing all the features of these models is discussed.     

Nondeterministic Temporal Relations in Multimedia Data

Synchronization is an important issue in multimedia systems which integrate a variety of temporally related media objects.One part of synchronization is the representation of temporal information.Wish the emerging interactive multimedia,deterministic temporal models are replaced by nondeterministic ones with more expressiveness.This paper classifies temporal models by their expressiveness,and evealuates relevant nondeterministic temporal relations in multimedia data.Additionally,an interval-based nondeterministic model based on a complete temporal operator set is proposed providing high-leval abstractions and a high degree of expressiveness for interactive multimedia systems.     

From case-based reasoning to traces-based reasoning

CBR is an original AI paradigm based on the adaptation of solutions of past problems in order to solve new similar problems. Hence, a case is a problem with its solution and cases are stored in a case library. The reasoning process follows a cycle that facilitates “learning” from new solved cases. This approach can be also viewed as a lazy learning method when applied for task classification. CBR is applied for various tasks as design, planning, diagnosis, information retrieval, etc. The paper is the occasion to go a step further in reusing past unstructured experience, by considering traces of computer use as experience knowledge containers for situation based problem solving.     

基于时态边缘算子的时间序列分段线性表示

时间序列的分段线性表示算法通常基于单一的启发式规则,难以适用于不同数据特征的时间序列。借鉴了边缘算子的思想来提取时间序列的边缘点,提出了一种基于时态边缘算子的时间序列分段线性表示算法。在来自不同领域的公开数据集上进行的实验结果表明：与两种主要的分段线性表示算法相比,该算法具有更好的拟合性能,并且更为稳定,能够适用于各类不同数据特征的时间序列。     

From event calculus to the scheduling problem. Semantics of action and temporal reasoning in aircraft maintenance

In this work we are interested in the logical and semantical aspects of reasoning about actions in a scheduling process. We present an adaptation of the event calculus of Kowalski and Sergot to the problem of determining the temporal structure of the operations that must be performed during the realization of some complex objectives. Our application domain is aircraft maintenance. We try to reason about the actions which are performed during an overhaul in order to help to schedule them. The original model reasons about changes, i.e. events which initiate or terminate propositions. The first step of this work was to improve the initial model by adding a temporal relation between events and propositions because in our field we also have to reason about events which only inform us about some propositions without affecting them. The second step of this work is to build a set of specific rules which temporally interpret the semantics of the usual specifications of the actions to be considered. This interpretation aims to associate each action with two events and some temporal relations which are usable by the general model. Temporal reasoning uses pertinent knowledge about the specific universe (here, the aircraft that we consider and the actions which may be performed on it). We outline a generative methodology to formalize this relevant knowledge efficiently. This cognitive approach brings more informational economy in temporal reasoning because only the relevant information is considered The temporal reasoning model and the methodology have been exemplified and tested on a complex part of an aircraft. In the future, adapted tools based on this approach will be developed, in order to solve several problems of aircraft maintenance scheduling.     

基于粗糙描述逻辑的不精确时态知识表示研究

在粗糙描述逻辑基础上扩充不精确时态关系,以满足不精确时态知识表示与推理的需要。首先给出了粗糙集及粗糙描述逻辑的相关概念;接着通过定义粗糙时态描述逻辑不精确时态关系,扩展了粗糙描述逻辑中具体域,并给出了可靠性和完备性证明;最后通过实际例子说明粗糙时态描述逻辑的知识表示和应用,结果表明扩展后的粗糙时态描述逻辑可以实现不精确时态知识的表示与推理。     

A different paradigm for expert systems: an introduction to logic programming and related knowledge representation issues

Abstract: Current expert system technology is 30 years old. Expert system shells find their origins in the work of early expert systems, most notably MYCIN which was developed at Stanford in the mid-1970s. Even Prolog programmers are settling for less robust reasoning power. The logic programming community (from which both expert systems and Prolog arose) has made notable advances since those times. These advances are lacking from current expert system technology. The advances include a well-developed theory of multiple forms of negation, an understanding of open domains and the closed world assumption, default reasoning with exceptions, reasoning with respect to time (i.e. a solution to the frame problem, and introspection with regard to previous beliefs), reasoning about actions, introspection, and maintaining multiple views of the world simultaneously.
The contribution of this paper is to discuss these developments in a singular, integrated, practical, digestible manner. Some of these ideas exist in a variety of papers spread across decades. They also exist in the minds of a very small community of researchers. Some of these ideas are unpublished. The presentation in this paper is from a different point of view, and intended to be more comprehensive and pedagogical. The presentation is also intended to be accessible to a much wider audience. Both the synthesis and the simplicity of this presentation are absent from the literature.     

Knowledge organization and its role in representation and interpretation for time-varying data: the ALVEN system

The so-called "first generation" expert systems were rule-based and offered a successful framework for building applications systems for certain kinds of tasks. Spatial, temporal, and causal reasoning, knowledge abstractions, and structuring are among topics of research for "second generation" expert systems. It is proposed that one of the keys for such research is knowledge organization. Knowledge organization determines control structure design, explanation and evaluation capabilities for the resultant knowledge base, and has strong influence on system performance. We are exploring a framework for expert system design that focuses on knowledge organization, for a specific class of input data, namely, continuous, time-varying data (image sequences or other signal forms). Such data are rich in temporal relationships as well as temporal changes of spatial relations, and are thus a very appropriate testbed for studies involving spatio-temporal reasoning. In particular, the representation formalism specifies the semantics of the organization of knowledge classes along the relationships of generalization/specialization, decomposition/aggregation, temporal precedence, instantiation, and expectation-activated similarity. Á hypothesize-and-test control structure is driven by the class organizational principles, and includes several interacting dimensions of search (data-driven, model-driven, goal-driven temporal, and failure-driven search). The hypothesis ranking scheme is based on temporal cooperative computation, with hypothesis "fields of influence" being defined by the hypothesis' organizational relationships. This control structure has proven to be robust enough to handle a variety of interpretation tasks for continuous temporal data. A particular incarnation, the ALVEN system, for left ventricular performance assessment from X-ray image sequences, will be summarized in this paper.     

A model of fuzzy spatio-temporal knowledge representation and reasoning based on high-level Petri nets

In many application areas there is a need to represent human-like knowledge related to spatio-temporal relations among multiple moving objects. This type of knowledge is usually imprecise, vague and fuzzy, while the reasoning about spatio-temporal relations is intuitive. In this paper we present a model of fuzzy spatio-temporal knowledge representation and reasoning based on high-level Petri nets. The model should be suitable for the design of a knowledge base for real-time, multi-agent-based intelligent systems that include expert or user human-like knowledge. The central part of the model is the knowledge representation scheme called FuSpaT, which supports the representation and reasoning for domains that include imprecise and fuzzy spatial, temporal and spatio-temporal relationships. The scheme is based on the high-level Petri nets called Petri nets with fuzzy spatio-temporal tokens (PeNeFuST). The FuSpaT scheme integrates the theory of the PeNeFuST and 117 spatio-temporal relations.The reasoning in the proposed model is a spatio-temporal data-driven process based on the dynamical properties of the scheme, i.e., the execution of the Petri nets with fuzzy spatio-temporal tokens. An illustrative example of the spatio-temporal reasoning for two agents in a simplified robot-soccer scene is given.     

结合CLIPS和VC++实现规则推理的方法

专家系统开发通常有三种方式：高级程序语言,专家系统外壳,专家系统工具。该文介绍了专家系统工具CLIPS6和高级程序语言VC++6.0的各自特点,提出了将专家系统工具CLIPS6与VC＋＋6.0高级语言编程工具结合起来开发专家系统,实现规则推理。详细描述了CLIPS嵌入VC++的一般过程：如何把CLIPS6嵌入VC++,如何加入CLIPS用户自定义函数来传递和返回参数。并以摩托车智能设计为例,详细阐述了规则编辑,事实获取,实现规则解释,实现人机交互功能等,从而实现摩托车智能设计的规则推理。     

面向维修专家系统中维修知识的组织与表达研究

针对复杂装备系统的特点,文章首先对复杂装备系统概念树的建立进行了描述,在建立概念树的基础上,提出了一种面向对象基于框架和规则集成的维修知识表示方法,最后给出了概念树维修对象的描述实例。     

Exact and approximate reasoning about temporal relations1

Allen gives an algebra for representing qualitative temporal information about the relationships between pairs of intervals. In this paper, we address a fundamental reasoning task that arises in applications of the algebra: Given (possibly indefinite) knowledge about the relationships between intervals, find all feasible relationships between two intervals. We call this the minimal labels problem. Finding the minimal labels can be viewed as computing the deductive consequences of our knowledge. Determining exact solutions to this problem has been shown to be (almost assuredly) intractable. Allen gives an approximation algorithm based on constraint propagation. We present new approximation algorithms; determine analytically under what conditions the algorithms are exact; and examine, through some computational experiments, the quality of the approximate solutions produced by the algorithms. We also give a simple test for predicting when the approximation algorithms will and will not produce good quality approximations. Finally, we survey three example applications of the interval algebra chosen from the literature to show where the results of this paper could be useful.     

Enhancing OODB semantics to support browsing in an OODB vocabulary representation

In previous work, we have modeled a vocabulary given as a semantic network by an object‐oriented database (OODB). The OODB schema thus obtained provides a compact abstract view of the vocabulary. This enables the fast traversal of the vocabulary by a user. In the semantic network vocabulary, the IS‐A relationships express the specialization hierarchy. In our OODB modeling of the vocabulary, the SUBCLASS relationship expresses the specialization hierarchy of the classes and supports the inheritance of their properties. A typical IS‐A path in the vocabulary has a corresponding shorter SUBCLASS path in the OODB schema. In this paper we expose several cases where the SUBCLASS hierarchy fails to fully correspond to the IS‐A hierarchy of the vocabulary. In these cases there exist traversal paths in the semantic network for which there are no corresponding traversal paths in the OODB schema. The reason for this failure is the existence of some IS‐A relationships between concepts of two classes, which are not connected by a SUBCLASS relationship. This phenomenon weakens the accuracy of our modeling. To rectify the situation we introduce a new OODB semantic relationship IS‐A to represent the existence of IS‐A relationships between concepts of a pair of classes which are not connected via a SUBCLASS relationship. The resulting schema contains both SUBCLASS relationships and IS‐A relationships which completely model the IS‐A hierarchy of the vocabulary. We define a mixed‐class level traversal path to contain either SUBCLASS or IS‐A relationships. Consequently, each traversal path in the semantic network has a corresponding mixed traversal path in the OODB schema. Hence the introduction of the semantic OODB IS‐A relationship improves the modeling of semantic network vocabularies by OODBs. Copyright © 2003 John Wiley & Sons, Ltd.     

模糊空间Petri网的规则表示及动态推理

为便于表示模糊空间Petri网的状态变迁规则,根据空间关联影响区域分布现实特点,提出了空间模糊Petri网中的状态关联影响规则、变迁关联影响规则和多阈值激活规则。依据模糊产生式规则的特点,详细描述了10种具体的推理规则和表示组件,并以实例加以说明。在此基础上,结合模糊空间Petri网的特点提出了动态推理过程算法,可以实现各种空间状态规则因子的转化。动态推理的过程不仅可以获取某种“结果”,而且可以挖掘基于空间位置关联的中间状态及引起中间状态变化的事件,可以有效地指导风险过程预测和控制。     

Truth Maintenance in Blackboard Environment

Constraint satisfaction and search problems generally fall into the class of problems for which a direct algorithmic solution does not exist. The solution of these problems requires the examination of state spaces. A problem solver (inference engine) alone is not able to organize and maintain state space consistently. For this purpose a so-called truth maintenance system is required. Our truth maintenance system (MEKON) organizes data within a data abstraction called a context . Each context corresponds to one problem state and contains currently believed data. The truth maintenance system provides believed data retrieval, belief revision, contradiction handling and non-monotonicity handling, the features that help a problem solver to examine state spaces. MEKON represents an ATMS-like system implemented within BEST (Blackboard-based Expert System Toolkit). However, some special MEKON features such as state variables, context sensitive generation of assumptions and explicit context generation, that are not present in standard ATMSs, facilitate not only the solution of constraint satisfaction problems, but also the solution of search problems (not provided by standard ATMSs). Being deeply integrated with Prolog/Rex, BEST's knowledge representation language, and BEST's inference engine, MEKON provides a simple and efficient means for the examination of state spaces. Facts, hypotheses (assumptions), and concepts (frames) are used to describe a problem state, contexts are used to represent points in the state spaces, while rules are used to perform state transitions. MEKON is the only truth maintenacne system that provides truth maintenance capabilities on local blackboards thus enabling the solution of complex problems which include different kinds of real constraint satisfaction and search problems concerning diagnosis, allocation tasks, classification tasks, planning or scenario making.