知识工程中使用演绎逻辑的局限性

本文简要归纳了演绎逻辑在知识工程中的作用,着重分析了演绎逻辑在知识表达、推理、问题求解、逻辑程序设计等方面以及作为专家系统说明语言与分析工具的局限性。     

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.     

一阶逻辑在关系数据库中的应用

一阶逻辑能唯一地作为关系数据库的统一语言，对关系数据库的可用性很多，本文主要讨论一些利用Prolog语言实现的应用。     

Querying datalog with arrays: Design and implementation issues

This paper deals with the implementation of logic queries where array structures are manipulated. Both top-down and bottom-up implementations of the presented logic language, called Datalog ^A , are considered. Indeed, SLD-resolution is generalized to realize Datalog ^A top-down query answering. Further, a fixpoint based evaluation of Datalog ^A queries is introduced, which forms the basis for efficient bottom-up implementation of queries obtained by generalizing rewriting techniques such as magic set method to the case of Datalog ^A programs.Work partially supported by a European Union grant under the EC-US project DEUS EX MACHINA: nondeterminism for deductive databases and by a MURST grant (40% share) under the project Sistemi formali e strumenti per basi di dati evolute.     

Verifying local stratifiability of logic programs and databases

In this paper, we deal with the problem of verifying local stratifiability of logic programs and databases presented by Przymusinski. The notion of dependency graphs is generalized from representing the priority relation between predicate symbols to representing the priority between atoms. Necessary and sufficient conditions for the local stratifiability of logic programs are presented and algorithms for performing the verification are developed. Finally, we prove that a database DB containing clauses with disjunctive consequents can easily be converted into a logic program P such that DB is locally stratified iff P is locally stratified. Yi-Dong Shen, Dr.: Department of Computer Science, Chongqing University, Chongqing, 630044, P.R. China (Present Address) c/o Ping Ran, Department of Heat Power Engineering, Chongqing UniversityResearch interests: Artificial Intelligence, Deductive Databases, Logic Programming, Non-Monotonic Reasoning, Parallel Processing     

关系数据库数字水印技术

随着知识产权保护和信息安全技术的发展,关系数据库数据存在所有权问题,可以采用数字水印技术对其进行数字所有权管理。该文分析了关系数据库中的数据和图像、声频、视频等多媒体数据的区别及关系数据库水印的特点,探讨了几种关系数据库数字水印技术,还分析了对关系数据库数据水印技术的攻击方式和理想的关系数据库水印技术。水印关系数据库对数据库的安全有着广阔前景和实际应用价值。     

A new deductive approach to planning

We introduce a new deductive approach to planning which is based on Horn clauses. Plans as well as situations are represented as terms and, thus, are first-class objects. We do neither need frame axioms nor state-literals. The only rule of inference is the SLDE-resolution rule, i.e. SLD-resolution, where the traditional unification algorithm has been replaced by anE-unification procedure. We exemplify the properties of our method such as forward and backward reasoning, plan checking, and the integration of general theories. Finally, we present the calculus and show that it is sound and complete. An earlier version of this paper was presented at the German Workshop on Artificial Intelligence, 1989.     

Reasoning About Data Provided By Federated Deductive Databases

This paper focuses on the problem of reasoning with information provided by a group of databases which share a common set of rules (deductive rules, integrity constraints). Each database is assumed to be consistent with the rules, but federating them may lead to contradictions. This paper describes a logic of beliefs, based on KD logic, for reasoning with contradictory information provided by several databases. It also presents a theorem prover, associated with this logic. This prover, described as a meta-interpreter of PROLOG allows us to derive formulas of the form: given the databases and the rules, assuming an order of relative reliability between the databases, is a given formula deducible? or, what are the individuals which satisfy a given formula? When the set of rules is not recursive, we prove the correctness of this theorem-prover.     

演绎数据库中完整性约束视图表示和生成算法

在演绎数据库系统中,一般将完整性约束条件和IDB规则分别表示和存储。文章基于笔者自行设计的SD-DDBS系统的IDB规则视图表示方法,给出了一个生成算法,将完整性约束条件表示成视图形式,克服了传统方法中存储开销大,演绎查询实现复杂的缺点,有效地提高了演绎查询的执行效率。     

Failure and Equality in Functional Logic Programming

Constructive failure has been proposed recently as a programming construct useful for functional logic programming, playing a role similar to that of constructive negation in logic programming. On the other hand, almost any functional logic program requires the use of some kind of equality test between expressions. We face in this work in a rigorous way the interaction of failure and equality (even for non-ground expressions), which is a non trivial issue, requiring in particular the use of disequality conditions at the level of the operational mechanism of constructive failure. As an interesting side product, we develop a novel treatment of equality and disequality in functional logic programming, by giving them a functional status, which is better suited for practice than previous proposals.     

Uncertain deductive databases: A hybrid approach

Uncertainty in deductive databases and logic programming has been modeled using a variety of (numeric and non-numeric) formalisms in the past, including probabilistic, possibilistic, and fuzzy set-theoretic approaches, and many valued logic programming. In this paper, we consider a hybrid approach to the modeling of uncertainty in deductive databases. Our model, called deductive IST (DIST) is based on an extension of the Information Source Tracking (IST) model, recently proposed for relational databases. The DIST model permits uncertainty to be modeled and manipulated in essentially qualitative terms with an option to convert qualitative expressions of uncertainty into numeric form (e.g., probabilities). An uncertain deductive database is modeled as a Horn clause program in the DIST framework, where each fact and rule is annotated with an expression indicating the “sources” contributing to this information and their nature of contribution. (1) We show that positive DIST programs enjoy the least model/least fixpoint semantics analogous to classical logic programs. (2) We show that top-down (e.g., SLD-resolution) and bottom-up (e.g., magic sets rewriting followed by semi-naive evaluation) query processing strategies developed for datalog can be easily extended to DIST programs. (3) Results and techniques for handling negation as failure in classical logic programming can be easily extended to DIST. As an illustration of this, we show how stratified negation can be so extended. We next study the problem of query optimization in such databases and establish the following results. (4) We formulate query containment in qualitative as well as quantitative terms. Intuitively, our qualitative sense of containment would say a query Q₁ is contained in a query Q₂ provided for every input database D, for every tuple t, t ε Q₂(D) holds in every “situation” in which t ε Q₁(D) is true. The quantitative notion of containment would say Q₁ is contained in Q₂ provided on every input, the certainty associated with any tuple computed by Q₁ is no more than the certainty associated with the same tuple by Q₂ on the given input. We also prove that qualitative and quantitative notions of containment (both absolute and uniform versions) coincide. (5) We establish necessary and sufficient conditions for the qualitative containment of conjunctive queries. (6) We extend the well-known chase technique to develop a test for uniform containment and equivalence of positive DIST programs. (7) Finally, we prove that the complexity of testing containment of conjunctive DIST queries remains the same as in the classical case when number of information sources is regarded as a constant (so, it's NP-complete in the size of the queries). We also show that testing containment of conjunctive queries is co-NP-complete in the number of information sources.     

归纳逻辑程序设计方法综述

归纳逻辑程序设计是机器学习与逻辑程序设计交叉所形成的一个研究领域,克服了传统机器学习方法的两个主要限制：即知识表示的限制和背景知识利用的限制,成为机器学习的前沿研究课题。首先从归纳逻辑程序设计的产生背景、定义、应用领域及问题背景介绍了归纳逻辑程序设计系统的概貌,对归纳逻辑程序设计方法的研究现状进行了总结和分析,最后探讨了该领域的进一步的研究方向。     

约束归纳逻辑程序设计方法的研究

提出了一种新的约束归纳逻辑程序设计方法。该方法能够与自顶向下的归纳逻辑程序设计系统结合,通过在自顶向下归纳方法的一步特殊化操作中引入Fisher判别分析等方法,使得系统能够导出不受变量个数限制的多种形式的线性约束,在不需要用户诱导,不依赖约束求解器的情况下,学习出覆盖正例而排斥负例的含约束的Horn子句程序。     

归纳逻辑程序设计综述

归纳逻辑程序设计是由机器学习与逻辑程序设计交叉所形成的一个研究领域,是机器学习的前沿研究课题。该文首先从归纳逻辑程序设计的问题背景、类型划分和搜索程序子句三个方面介绍了归纳逻辑程序设计系统的概貌;然后结合实验室的相关研究工作,回顾了归纳逻辑程序设计研究的发展;之后介绍了归纳逻辑程序设计领域中需要深入研究的若干问题,并提出了新的解决思路;最后是总结,以引起读者对归纳逻辑程序设计领域研究的进一步关注。     

演绎数据库系统中推理机的设计与实现

演绎推理是有效实现演绎数据库系统的关键与核心,该文针对一种结构合理的演绎数据库系统的设计方案,介绍了系统中实现递归查询的推理机的设计原理及实现过程中用到的优化技术,并对推理机的运行机制进行了分析。     

Unfolding-based Improvements on Fuzzy Logic Programs

Unfolding is a semantics-preserving program transformation technique that consists in the expansion of subexpressions of a program using their own definitions. In this paper we define two unfolding-based transformation rules that extend the classical definition of the unfolding rule (for pure logic programs) to a fuzzy logic setting. We use a fuzzy variant of Prolog where each program clause can be interpreted under a different (fuzzy) logic. We adapt the concept of a computation rule, a mapping that selects the subexpression of a goal involved in a computation step, and we prove the independence of the computation rule. We also define a basic transformation system and we demonstrate its strong correctness, that is, original and transformed programs compute the same fuzzy computed answers. Finally, we prove that our transformation rules always produce an improvement in the efficiency of the residual program, by reducing the length of successful Fuzzy SLD-derivations.     

基于SQL Server的演绎数据库系统

分析了演绎数据库的理论基础和实现机制,重点介绍设计和实现的基于SQL Server的演绎数据库系统,对系统进行了分析和评价。     

Using Constraint Programming in Selection Operators for Constraint Databases

Constraint Databases represent complex data by means of formulas described by constraints (equations, inequations or Boolean combinations of both). Commercial database management systems allow the storage and efficient retrieval of classic data, but for complex data a made-to-measure solution combined with expert systems for each type of problem are necessary. Therefore, in the same way as commercial solutions of relational databases permit storing and querying classic data, we propose an extension of the Selection Operator for complex data stored, and an extension of SQL language for the case where both classic and constraint data need to be managed. This extension shields the user from unnecessary details on how the information is stored and how the queries are evaluated, thereby enlarging the capacity of expressiveness for any commercial database management system. In order to minimize the selection time, a set of strategies have been proposed, which combine the advantages of relational algebra and constraint data representation.     

Static and Dynamic Slicing of Constraint Logic Programs

Slicing is a program analysis technique originally developed for imperative languages. It facilitates understanding of data flow and debugging.This paper discusses slicing of Constraint Logic Programs. Constraint Logic Programming (CLP) is an emerging software technology with a growing number of applications. Data flow in constraint programs is not explicit, and for this reason the concepts of slice and the slicing techniques of imperative languages are not directly applicable.This paper formulates declarative notions of slice suitable for CLP. They provide a basis for defining slicing techniques (both dynamic and static) based on variable sharing. The techniques are further extended by using groundness information.A prototype dynamic slicer of CLP programs implementing the presented ideas is briefly described together with the results of some slicing experiments.     

演绎型面向对象数据库管理系统形式模型研究

本文提出了一种研制演绎型面向对象数据库管理系统(DOODBMS)的理论基础,具体讨论了DOODBMS 的形式化描述、操作以及知识引入等问题,使得一方面,实现一般面向对象数据库管理系统(OODBMS)的功能,另一方面,又可获得OODBMS 的推理智能