A Prolog Rule-Based System for cartographic Name Placement

Manual name placement is an extremely time consuming task and has been one of the most difficult aspects of the map production process to automate. It is complicated by the large number of rules required for the selection and placement of names. A hybrid Prolog/Fortrau rule-based system is described for placing names on a variety of map types. It uses a set of Prolog primitives for spatial search and name placement operations. The Ordnance Survey's 1:625000 scale digital dataset has been used to illustrate the application of rules for the selection of labels as well as for controlling their size and orientation. The application to other types of maps and diagrams is also briefly described.     

Logichart — Intelligible Program Diagram for Prolog and its Processing System

An intelligible program diagram called Logichart has been developed for Prolog visualization. Its syntax rules and layout rules are formalized in terms of an attribute graph grammar. This grammar is underlain by a context–free graph grammar whose productions are defined to formalize the graph–syntax rules of Logichart diagrams. Semantic rules attached to the productions are defined in such a way that they can extract the layout information needed to display a Logichart diagram as attributes. Our Prolog visualization system, which has been implemented based on the attribute graph grammar, can draw a Logichart diagram for any correct Prolog program (completeness), and any Logichart diagram displayed by the system is always valid for the grammar (soundness). The system can also display the execution of a Prolog program in real time; that is, the Logichart diagram is dynamically updated as the program runs.     

基于混合推理的知识库的构建及其应用研究

该文提出了基于OWL本体与Prolog规则的平面几何知识库的构建方法,从而可形式化地表示平面几何中丰富的语义信息.一方面,用类型、定义域、值域、分类、属性、实例等本体描述来表达结构化的知识,为领域内概念与概念之间关系的描述提供形式化的语义;另一方面,用Prolog规则来解决本体不能有效表达的诸如属性之间的关系和操作等问题,从而支持复杂关系间的推理.在此基础上,用Protégé和Prolog构建了一个基于本体和规则的平面几何知识库.实验证明:此知识库可实现知识和语义层次上的信息查询,还可进行复杂问题求解,其丰富的语义描述和混合推理能力弥补了传统知识库的不足.     

Record manipulation in prolog

Prolog is a relatively new programming language that has proved excellent for symbolic computation. However, Prolog was not specifically designed for industrial scale work and it lacks some standard features that are useful for reading, maintaining and debugging large programs. In particular, Prolog has no record mechanism, and programs often require major changes when data structures are modified. The record is a standard data abstraction concept that improves the robustness of programs. The main advantage in using records is that data structures can be modified and extended with minimal repercussion to program code. Furthermore, the use of significant names to access data fields means that the intent of code is generally clearer. We present a set of primitive operators that support a readable and robust programming style for the manipulation of record data structures in standard Prolog. The proposal covers both simple and imbricated record types and handles selective modification of records cleanly. We also treat property lists and records in a uniform way. These benefits are achieved with minimal overhead while retaining the traditional Prolog non-deterministic style.     

Prolog/Rex-a way to extend Prolog for better knowledgerepresentation

Prolog/Rex represents a powerful amalgamation of the latest techniques for knowledge representation and processing, rich in semantic features that ease the difficult task of encoding heterogeneous knowledge of real-world applications. The Prolog/Rex concept mechanism lets a user represent domain entities in terms of their structural and behavioral properties, including multiple inheritance, arbitrary user-defined relations among entities, annotated values (demons), incomplete knowledge, etc. A flexible rule language helps the knowledge engineer capture human expertise and provide flexible control of the reasoning process. Additional Prolog/Rex strength that cannot be found in any other hybrid language made on top of Prolog is language level support for keeping many potentially contradictory solutions to a problem, allowing possible solutions and their implications to be automatically generated and completely explored before they are committed. The same mechanism is used to model time-states, which are useful in planning and scheduling applications of Prolog/Rex     

High-performance logic programming with the Aquarius Prologcompiler

Aquarius Prolog, a high performance compiler designed and built to test the hypothesis that Prolog can be implemented as efficiently as an imperative language by compiling the more powerful features of logic programming only where they are needed, and then only in the simplest form, is described. The authors begin with some background on logic programming and then discuss the Prolog language in more detail. They present an overview of their compiler, giving its structure and the principles underlying its high performance. They compare their system with two popular high-performance commercial systems and with two implementations of C and conclude with an overview of ways to extend this work     

Regular corecursion in Prolog

Corecursion is the ability of defining a function that produces some infinite data in terms of the function and the data itself, as supported by lazy evaluation. However, in languages such as Haskell strict operations fail to terminate even on infinite regular data, that is, cyclic data.Regular corecursion is naturally supported by coinductive Prolog, an extension where predicates can be interpreted either inductively or coinductively, that has proved to be useful for formal verification, static analysis and symbolic evaluation of programs.In this paper we use the meta-programming facilities offered by Prolog to propose extensions to coinductive Prolog aiming to make regular corecursion more expressive and easier to program with.First, we propose a new interpreter to solve the problem of non-terminating failure as experienced with the standard semantics of coinduction (as supported, for instance, in SWI-Prolog). Another problem with the standard semantics is that predicates expressed in terms of existential quantification over a regular term cannot directly defined by coinduction; to this aim, we introduce finally clauses, to allow more flexibility in coinductive definitions.Then we investigate the possibility of annotating arguments of coinductive predicates, to restrict coinductive definitions to a subset of the arguments; this allows more efficient definitions, and further enhance the expressive power of coinductive Prolog.We investigate the effectiveness of such features by showing different example programs manipulating several kinds of cyclic values, ranging from automata and context free grammars to graphs and repeating decimals; the examples show how computations on cyclic values can be expressed with concise and relatively simple programs.The semantics defined by these vanilla meta-interpreters are an interesting starting point for a more mature design and implementation of coinductive Prolog.     

Formal reasoning in intelligent database systems

Expert database systems were proposed to solve the difficulties encountered in traditional database systems. Prolog provides a fast prototyping tool for building such database systems. However, an intelligent database system implemented in Prolog faces a major restriction that only Horn rules are allowed in the knowledge base. We propose a theorem prover which can make inference for non-Horn intelligent database systems. Conclusions can be deduced from the facts and rules stored in a knowledge base. For a knowledge base with a finite domain, the prover can provide correct answers to queries, derive logical consequences of the database, and provide help in detecting inconsistencies or locating bugs in the database. The theorem prover is efficient in deriving conclusions from large knowledge bases which might swamp most of the other deductive systems. The theorem prover is also useful in solving heuristically the satisfiability problem related to a database with an infinite domain. A truth maintenance mechanism is provided to help eliminate repetitious work for the same goals.Supported by National Science Council under grant NSC 81-0408-E-110-9.     

The "Software Engineering" of Expert Systems: Is Prolog Appropriate?

This paper is a preliminary assessment of the viability of Prolog as a basis for the design of expert systems, where the major competition is assumed to be from Lisp and Lisp-based systems. We critically examine the basic features of Prolog from various perspectives to see to what extent they support (or hinder) expert system development. Our conclusion is that while Prolog has significant assets along several dimensions, Prolog as it exists today needs to be modified and appropriately enhanced to make it competitive to extant Lisp-based systems; we suggest the nature of some of these modifications.     

Critical factors in the evolution of logic programming and Prolog

Logic programming has received much critical attention over the past two decades from both a language perspective and as a methodology for practical problem solving. This paper presents a historical foundation of the approach and examines the development of Prolog since its first implementation. An analysis of the use of Prolog in commercial, research and teaching environments shows that there is an established base of users and that, after a period of rapid growth, the language currently enjoys continuing activity. The key to its success so far is due to its continuing evolution by including features that were not seen as being within the original concept as a pure logic language. Significant features which have contributed to the success of Prolog include integration with other languages, object oriented extensions, constraint representation, parallel execution as well as improved speed and robustness. Applications databases are analysed with respect to type of application, system status, type of developer, hardware platform, country of origin and the Prolog implementation used. Factors contributing to the success of Prolog are identified and likely future developments are explored.     

Operational and goal-independent denotational semantics for Prolog with cut

In this paper we propose an operational and a denotational semantics for Prolog. We deal with the control rules of Prolog and the cut operator. Our denotational semantics provides a goal-independent semantics. This means that the behaviour of a goal in a program is defined as the evaluation of the goal in the denotation (semantics) of the program. We show how our denotational semantics can be specialised into a computed answer semantics and into a call pattern semantics. Our work provides a basis for a precise abstract interpretation of Prolog programs.     

Regulation management and logic programming

Regulations are pervasive in information systems. They manifest themselves as design rules, integrity constraints, deadlines, conventions, information disclosure requirements, policies, procedures, contracts, taxes, quotas and other statutes. Managing regulations is difficult. Regulations are complex, change frequently and rest on models of the real world that involve unusual vocabulary if not unusual concepts. Consequently, checking compliance with regulations is tedious and error-prone. Logic programming appears to provide a good framework for developing regulation management systems. Besides permitting arbitrary regulations to be modelled, it offers rapidity and ease of development, readability, incremental modifiability, extensibility and portability. These features are not provided by existing DP programming tools, database managers or conventional expert-system shells. This paper investigates the application of logic programming in a significant regulation management application: Workers' Compensation Insurance premium auditing. The insurance premium computation rules for the State of California were encoded as a large Prolog program. This application illustrates specific strengths and weaknesses of logic programming and Prolog in dealing with large-scale real-world regulations.     

Frame-based system for image interpretation

This paper describes a frame-based computer vision system named FABIUS implemented in Prolog. Advantages of using frames for computer vision are that they are modular and understandable; structural, decomposable objects can be described by part frame hierarchies, and specialization frame hierarchies enable property inheritance and flexible, efficient object classification. Image processing operations, written in C, are triggered as demons when specific slots in a frame are accessed. Prolog provides the problem solving facilities of backtracking and pattern matching. The system is shown to be well suited to rapid development of applications and alternative interpretation strategies, and its operation is illustrated when applied to the task of identifying vehicles in cluttered real-world scenes.     

POPE — a parallel-operating prolog engine

An architecture is presented for the parallel execution of sequential Prolog. The architecture is based on a pipeline of unification processors and designed to work as a co-processor to a more conventional, UNIX based workstation. The unification processors execute highly optimized compiled Prolog code; however, the basic concept of the architecture could also increase the performance of interpreter based systems. It will be shown that even programs that do not exhibit any of the ‘classical’ forms of parallelism (i.e. AND-, OR-parallelism, etc.) can be effectively mapped onto the proposed architecture. The presented architecture should also prove very effective as a multi-user Prolog machine executing several independent Prolog programs in parallel. In contrast to other attempts to execute sequential Prolog in parallel we do not restrict the use of any of the standard Prolog language features such as dynamic assert/retract, CUT, etc. Simulation results show that peak execution rates of over 1000 KLIPS can be obtained.     

P#: a concurrent Prolog for the .NET framework

We discuss P#, our implementation of a tool that allows interoperation between a concurrent superset of the Prolog programming language and C#. This enables Prolog to be used as a native implementation language for Microsoft's .NET platform. P# compiles a linear logic extension of Prolog to C# source code. We can thus create C# objects from Prolog and use C#'s graphical, networking and other libraries. We add language constructs on the Prolog side that allow concurrent Prolog code to be written. A primitive predicate is provided that evaluates a Prolog structure on a newly forked thread. Communication between threads is based on the unification of variables contained in such a structure. It is also possible for threads to communicate through a globally accessible table. All of the new features are available to the programmer through new built-in Prolog predicates. We discuss two software engineering tools implemented using P#. Copyright © 2004 John Wiley & Sons, Ltd.     

维吾尔语中汉族人名的识别及翻译

该文研究了一种维吾尔语中汉族人名的识别和翻译方法。该方法在词典等传统方法的基础上,运用语言模型实现维语中的汉族人名的识别和翻译。针对维语人名的构词和拼写特点,增加了名词词缀识别预处理模块,补充了维语字母到汉语拼音的映射规则,有效提高了人名识别的正确率及召回率。在1 000句含有汉族人名的维语语料上进行测试,汉族人名识别的正确率和召回率分别达到75.2%和91.5%。     

BUP: A Bottom-Up parser embedded in Prolog

A parser based on logic programming language (DCG) has very useful features; perspicuity, power, generality and so on. However, it does have some drawbacks in which it cannot deal with CFG with left recursive rules, for example. To overcome these drawbacks, a Bottom-Up parser embedded in Prolog (BUP) has been developed. In BUP, CFG rules are translated into Prolog clauses which work as a bottom-up left corner parser with top-down expectation. BUP is augmented by introducing a “link” relation to reduce the size of a search space. Furthermore, BUP can be revised to maintain partial parsing results to avoid computational duplication. A BUP translator and a BUP tracer which support the development of grammar rules are described.     

CGLIB—a constraint‐based graphics library

CGLIB is a high‐level graphics library for B‐Prolog, a constraint logic programming system. The library provides primitives for creating and manipulating graphical objects and a set of constraints including not‐overlap, grid, table and tree constraints that facilitate the specification of the layouts of objects. The library adopts a construct called action rules which is available in B‐Prolog for creating agents and programming interactions among agents or between agents and the user. The library is a fully working system implemented in B‐Prolog, Java and C. It can be used in many areas such as drawing editors, interactive user interfaces, document authoring, animation, information visualization, intelligent agents and games. The high‐level abstraction of the library and the use of constraints and action rules in the specification of layouts and behaviors can significantly enhance the productivity of the development of graphics. We demonstrate through several examples the effectiveness of the library as a tool for developing graphics‐rich and interactive user interfaces. Copyright © 2003 John Wiley & Sons, Ltd.     

UCB策略在Prolog中的应用

Prolog(Programming in Logic)程序语言是一种逻辑程序设计语言.它是在逻辑学理论基础上建立起来的并广泛应用在人工智能研究中.这几十年已经出现了各具特色的Prolog编译器,而且各种编译器也都很成功.虽然在现阶段已经出现了各种版本Prolog编译器,但是Prolog编译器的发展空间还是很大.本文先通过现代Prolog编译器的不足,介绍了新Prolog编译器的特点,然后简单叙述了Prolog编译器词法分析和语法分析的过程,最后介绍了UCB策略.