模糊Prolog系统

模糊Prolog系统将不确定性引入到传统的Prolog系统中,对现实应用具有很大的意义。文中首先介绍了模糊系统和Prolog系统,然后讨论了实现模糊Prolog系统的两种方法,并给出了一些典型的模糊Prolog模型。最后重点讨论了在Prolog系统中实现模糊集合的几种方法,因而对于不同的应用要求可以选择不同类型的模糊Prolog系统。     

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.     

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.     

QD-Janus: A sequential implementation of Janus in Prolog

Janus is a language designed for distributed constraint programming. This paper describes QD-Janus, a sequential implementation of Janus in Prolog. The compiler uses a number of novel analyses and optimizations to improve the performance of the system. The choice of Prolog as the target language for a compiler, although unusual, is motivated by the following: (i) the semantic gap between Janus and Prolog is much smaller than that between Janus and, say, C or machine language—this simplifies the compilation process significantly, and makes it possible to develop a system with reasonable performance fairly quickly; (ii) recent progress in Prolog implementation techniques, and the development of Prolog systems whose speeds are comparable to those of imperative languages, indicates that the translation to Prolog need not entail a significant performance loss compared to native code compilers; and (iii) compilation to Prolog can benefit immediately from a significant body of work on, and implementations of, parallel Prolog systems. Our experience indicates that translation of logic programming languages to Prolog, accompanied by the development of good program analysis and optimization tools, is an effective way to quickly develop flexible and portable implementations with good performance and low cost.     

Full prolog and scheduling or-parallelism in muse

Muse is a simple and efficient approach to Or-parallel implementation of the full Prolog language. It is based on havingmultiplesequential Prolog engines, each with its local address space, and some shared memory space. It is currently implemented on a number of bus-based and switch-based multiprocessors. The sequential SICStus Prolog system has been adapted to Or-parallel implementation with very low extra overhead in comparison with other approaches. The Muse performanhce results are very encouraging in absolute and relative terms.The Muse execution model and its performance results on two different multiprocessor machines for a parallel version of Prolog, named Commit Prolog, have been presented in previous papers. This paper discusses supporting the full Prolog language and describes mechanisms being developed for scheduling Or-parallelism in Muse. It also presents performance results of the Muse implementation on Sequent Symmetry after supporting full Prolog. The results show that the extra overhead associated with supporting the full Prolog language is negligible.     

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     

Prolog逻辑程序的测试方法

Prolog逻辑程序设计语言具有不同于传统程序设计语言的特点.本文根据测试Prolog程序的实践,提出了一系列为Prolog程序生成测试用例的准则.按这些准则测试实际程序效果良好.这是在逻辑程序测试新领域迈出的一步.     

Translating a Linear Logic Programming Language into Java

There have been several proposals for logic programming language based on linear logic: Lolli [8], Lygon [7], LO [3], LinLog [2], Forum [11], HACL [10]. In these languages, it is possible to create and consume resources dynamically as logical formulas. The efficient handling of resource formulas is, therefore, an important issue in the implementation of these languages. Lolli, Lygon, and Forum are implemented as interpreter systems; Lolli is on SML and λProlog, Lygon is on Prolog, Forum is on SML, λProlog and Prolog. However, none of them have been implemented in Java.In this paper, we describe the Prolog Café ¹ system which translates a linear logic programming language called LLP to Java via the LLPAM [12] [5], an extension of the standard WAM [16] [1] for LLP. LLP is a superset of Prolog and a subset of Lolli. The main difference from the first implementation [4] is resource compilation. That is to say, resource formulas are compiled into closures which consist of a reference of compiled code and a set of bindings for free variables. Calling these resources is integrated with the ordinary predicate invocation.Prolog Café is portable to any platform supporting Java and easily expandable with increasing Java's class libraries. In performance, on average, Prolog Café generate 2.2 times faster code for a set of classical Prolog benchmarks compared with jProlog.     

Logic programming and compiler writing

The concept of ‘logic programming’, and its practical application in the programming language Prolog, are explained from first principles. The ideas are illustrated by describing in detail one sizable Prolog program which implements a simple compiler. The advantages and practicability of using Prolog for ‘real’ compiler implementation are discussed.     

Prology程序部分计算的研究与实现

部分计算是一种重要的程序变换方法和编译优化技术，Prolog程序特别适合于部分计算。目前，国际上已开始了几个Prolog程序部分计算的原理模型和专用工具，但其中存在以下若于问题:(1)关于Prolog程序部分计算的基本原理和特征缺乏系统的认识;(2)现有的两种检测逻辑程序中循环的方法，并没有最后解决部分计算的终止性问题》;(3)关于Prolog中内部谓词的处理不够究善，而且其中还隐含了许多语叉错误;(4)部分计算算法相当低效；(5)现有的部分计算器局限于各自的应用领域，缺乏通用性。本文结合我们研制GKD－Prolog编译系统[14]剖中一个实用源级部分计算器的工作实践，全面、系统地讨论了纯Prolog的部分计算、逻辑程序的循环检测以及全Prolog的内部谓词处理。     

A pragmatic type concept for Prolog supporting polymorphism, subtyping, and meta-programming

Approaches to typing logic programs often exclude various features of Standard Prolog. The system “Typical for annotated Prolog” (TaP) is a pragmatic approach to type checking programs written in Prolog without restricting the scope of the language. TaP checks Prolog programs that are extended with type declarations that support parametric polymorphism and subtyping. The purpose of this paper is to present an approach that extends Typical by meta-types for handling Prolog meta-programming techniques.     

High-level management of computation history for the design and implementation of a prolog system

We present the implementation of a Prolog system composed of interpreter and compiler. The originality of our work consists in the adoption of a new framework to realize the main components of the system. The framework relies on new mechanisms, called sleepers. With their help we have developed a complete Prolog interpreter in which all the control activities, from backtracking up to last-call optimization, are performed by the sleeper mechanism. We have also produced a Prolog compiler by using a philosophy and tactics that are completely independent of hardware constraints; it exploits an incremental and abstract implementation technique, based on a delayed non-local execution protocol. Our approach to Prolog system implementation has been extremely useful both in terms of software design and overall performance.     

Debugging Prolog Using Annotations

We present an annotation language well-suited for rendering aspects of Prolog execution. Our annotations are special Prolog goals that act as executable comments, performing debugging at run-time. No restrictions are placed upon the object language, the concern being verification of (full) Standard Prolog programs. Here we discuss the merits of the annotations for Prolog debugging. All the examples are actual runs of our system, Nope.     

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.     

Efficient reordering of Prolog programs

Prolog programs are often inefficient: execution corresponds to a depth-first traversal of an AND/OR graph; traversing subgraphs in another order can be less expensive. It is shown how the reordering of clauses within Prolog predicates, and especially of goals within clauses, can prevent unnecessary search. The characterization and detection of restrictions on reordering is discussed. A system of calling modes for Prolog, geared to reordering, is proposed, and ways to infer them automatically are discussed. The information needed for safe reordering is summarized, and which types can be inferred automatically and which must be provided by the user are considered. An improved method for determining a good order for the goals of Prolog clauses is presented and used as the basis for a reordering system     

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.     

Algebraic computational models of OR-parallel execution of Prolog

A specification of the OR-parallel execution of Prolog programs, using CHOCS (calculus of higher order communicating systems) [24], is presented in the paper. A translation is defined from Prolog programs and goals to CHOCS processes: the execution of the CHOCS process corresponding to a goal mimics the OR-parallel execution of the original Prolog goal. In the translation, clauses and predicate definitions of a Prolog program correspond to processes. To model OR-parallelism, the processes , corresponding to clauses (having the same head predicate ) start their execution concurrently, but, in order to respect the depth-first search rule, each is guarded by the termination of the executions of processes 's, . The computational model is proved correct with respect to the semantics of Prolog, as given in [4, 5]. Our model, because of its algebraic specification, can be easily used to prove properties of the parallel execution of Prolog programs. Moreover, the model exploits the maximum degree of parallelism, by giving the Prolog solutions in parallel, without any order among them. However, this model, being close to the Prolog semantics definition, contains sources of inefficiency which make it unpractical as a guide for the implementation. To overcome these problems, a new computational model is defined. This model is obtained by modifications of the basic one and thus its correctness can be easily proved. Finally, we show how to obtain models of different real implementations of OR-parallel Prolog by slight modification of the new model. The relations among all these models, in terms of parallelism degree, are studied by using the concepts of bisimulation and simulation, developed for concurrent calculi. Received: 5 May 1995 / 28 May 1996     

An Operator Precedence Parser for Standard Prolog Text

Prolog is a language with a dynamic grammar which is the result of embedded operator declarations. The parsing of such a language cannot be done easily by means of standard tools. Most often, an existing parsing technique for a static grammar is adapted to deal with the dynamic constructs. This paper uses the syntax definition as defined by the ISO standard for the Prolog language. It starts with a brief discussion of the standard, highlighting some aspects that are important for the parser, such as the restrictions on the use of operators as imposed by the standard in order to make the parsing deterministic. Some possible problem areas are also indicated. As output is closely related to input in Prolog, both are treated in this paper. Some parsing techniques are compared and an operator precedence parser is chosen to be modified to deal with the dynamic operator declarations. The necessary modifications are discussed and an implementation in C is presented. Performance data are collected and compared with a public domain Prolog parser written in Prolog. It is the first efficient public domain parser for Standard Prolog that actually works and deals with all the details of the syntax.     

Focal structures and information types in Prolog

Several studies have suggested that the mental structures of programmers of procedural languages have a close relationship with a model of structural knowledge related to functional information known as programming Plans. It also has been claimed that experienced programmers organize this representation in a hierarchical structure where some elements of Plans are focal or central to them. However, it is not clear that this is the case for other types of programming languages, especially for those which are significantly different from the procedural paradigm.The study reported in this paper investigates whether these claims are true for Prolog, a language which has important differences to procedural languages. Prolog does not have obvious syntactic cues to mark blocks of code (begin/end, repeat/until, etc). Also, its powerful primitives (unification and backtracking) and the extensive use of recursion might influence how programmers comprehend Prolog code in a significant way.The findings of the study suggest that Plans and functional information are important for Prolog programmers, but that there is also at least another model of structural knowledge valid for this language. This model of structural knowledge, Prolog schemas, is related to data structure information and it seems that a hierarchical organisation that highlights the relevance of some of its elements as focal is valid for Prolog. These results support the view that comprehension involves the detection of varying aspects of the code and that each of the structures related to these aspects might have their own organization and hierarchical relations.