Extending Prolog with modularity,concurrency and meta-rules

This paper presents the main features of an extension to Prolog toward modularity and concurrency—calledCommunicating Prolog Units (CPU)—whose main aim is to allow logic programming to be used as an effective tool for system programming and prototyping. While Prolog supports only a single set of clauses and sequential computations, CPU allows programmers to define different theories (P-unis) and parallel processes interacting via P-units, according to a model very similar to Linda’s generative communication. The possibility of expressingmeta-rules to specify where and how object-level (sub)golas have to be proved, not only enhances modularity, but also increases the expressive power and flexibility of CPU systems.     

PAN: A portable,parallel Prolog: Its design,realisation and performance

PAN is a general purpose, portable environment for executing logic programs in parallel. It combines a flexible, distributed architecture which is resilient to software and platform evolution with facilities for automatically extracting and exploiting AND and OR parallelism in ordinary Prolog programs. PAN incorporates a range of compile-time and run-time techniques to deliver the performance benefits of parallel execution while rertaining sequential execution semantics. Several examples illustrate the efficiency of the controls that facilitate the execution of logic programs in a distributed manner and identify the class of applications that benefit from distributed platforms like PAN. George Xirogiannis, Ph.D.: He received his B.S. in Mathematics from the University of Ioannina, Greece in 1993, his M.S in Artificial Intelligence from the University of Bristol in 1994 and his Ph.D. in Computer Science from Heriot-Watt University, Edinburgh in 1998. His Ph.D. thesis concerns the automated execution of Prolog on distributed heterogeneous multi-processors. His research interests have progressed from knowledge-based systems to distributed logic programming and data mining. Currently, he is working as a senior IT consultant at Pricewaterhouse Coopers. He is also a Research Associate at the National Technical University of Athens, researching in knowledge and data mining. Hamish Taylor, Ph.D.: He is a lecturer in Computer Science in the Computing and Electrical Engineering Department of Heriot-Watt University in Edinburgh. He received M.A. and MLitt degrees in philosophy from Cambridge University and an M.S. and a Ph.D. degree in computer science from Heriot-Watt University, Scotland. Since 1985 he has worked on research projects concerned with implementing concurrent logic programming languages, developing formal models for automated reasoning, performance modelling parallel relational database systems, and visualisizing resources in shared web caches. His current research interests are in applications of collaborative virtual environments, parallel logic programming and networked computing technologies.     

Introduction of dosim predicate to Prolog

This paper proposes a predicate nameddosim which provides a new function for parallel execution of logic programs. The parallelism achieved by this predicate is a simultaneous mapping operation such as bagof and setof predicates. However, the degree of parallelism can be easily decided by arranging the arguments of the dosim goal. The parallel processing system with dosim was realized on a tight-coupled multiprocessor machine. To control the degree of parallelism and reduce the amount of memory required for execution, we introduce the grouping method for the goals executed in parallel and some variations of the dosim predicate. The effectiveness of the proposed method is demonstrated by the results of the execution of several applications.     

A Prolog simulator for deterministic P systems with active membranes

In this paper we propose a new way to represent P systems with active membranes based on Logic Programming techniques. This representation allows us to express the set of rules and the configuration of the P system in each step of the evolution as literals of an appropriate language of first order logic. We provide a Prolog program to simulate, the evolution of these P systems and present some auxiliary tools to simulate the evolution of a P system with active membranes using 2-division which solves the SAT problem following the techniques presented in Reference.¹⁰ Andrés Cordón-Franco: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Mathematical Logic, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical (software implementation) point of view. Miguel A. Gutiérrez-Naranjo: He is an assistant professor in the Computer Science and Artificial Intelligence Department at University of Sevilla, Spain. He is also a member of the Research Group on Natural Computing of the University of Seville. His research interest includes Machine Learning, Logic Programming and Membrane Computing, both from a theoretical and a practical point of view. Mario J. Pérez-Jiménez, Ph.D.: He is professor of Department of Computer Science and Artificial Intelligence at University of Seville, where he is the head of the Group of Research on Natural Computing, He has published 8 books of Mathematics and Computation, and more than 90 scientific articles in prestigious scientific journals. He is member of European Molecular Computing Consortium. Fernando Sancho-Caparrini: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Complex Systems, DNA Computing, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical point of view.     

How should Prolog computation Be represented for practical use?

We propose a visual computation model called theBox and Plane Model (BPM), which visually clarifies the semantics of backtracking, the cut operator, and side-effects, thus allowing the procedural features of Prolog to be grasped. On the bases of the BPM, we developed a visual debugger for Prolog, PROEDIT2, which has proved that this kind of pragmatic computation model for Prolog increases the efficiency of the debugging work.     

The programming language standards scene, ten years on Paper 13: Prolog

This paper, one of a simultaneously published set, describes the establishment in 1984 of the standards project for the programming language Prolog, and subsequent progress of the project, which at the end of 1993 is almost complete. This brief overview of the forthcoming standard concentrates on issues of general interest: for example, concepts such as unification and a user-defined syntax are being standardized for the first time. Their definitions can and should be re-used in the standard for any other language which includes these concepts.     

An application of an OR-Parallel Prolog system to phylogenetic analysis

In this paper we discuss an application of our OR-Parallel Prolog system to a search problem of importance in practice: the construction of phylogenetic trees. The use of a maximum likelihood method to construct such trees is based on concrete models of evolutional processes and is well-motivated statistically. However, the use of maximum likelihood methods has been hindered by the computational cost to calculate the likelihood of possible alternative trees (i.e. their confidence scores) at each search step for the optimal tree. To cope with this problem, we used OR-parallel Prolog as a coordination language to orchestrate the search for the optimal tree. A numerical computation written in C computed the likelihood of each alternative tree and a symbolic computation written in Prolog performed a parallel A* tree search. For constructing phylogenetic trees of bacterial organisms, our parallel algorithm allowed us to increase the size of the search space, allowing us to include nearly optimal as well as optimal intermediate trees in the search. Our priority mechanism reduced the generation of useless tasks and resulted in superlinear speedups in some cases.     

递归算法在C语言程序设计中的实现

本文根据递归算法的定义，对其在C语言程序设计中的应用进行了阐述，通过对递归的内部实现过程的描述，对递归的使用进行评价，说明递归在程序设计中具有一定的使用空间．     

递归算法在C语言程序设计中的实现

本文根据递归算法的定义,对其在C语言程序设计中的应用进行了阐述,通过对递归的内部实现过程的描述,对递归的使用进行评价,说明递归在程序设计中具有一定的使用空间.     

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.     

On the equivalence and range of applicability of graph-based representations of logic programs

Logic programs under Answer Sets semantics can be studied, and actual computation can be carried out, by means of representing them by directed graphs. Several reductions of logic programs to directed graphs are now available. We compare our proposed representation, called Extended Dependency Graph, to the Block Graph representation recently defined by Linke [Proc. IJCAI-2001, 2001, pp. 641-648]. On the relevant fragment of well-founded irreducible programs, extended dependency and block graph turns out to be isomorphic. So, we argue that graph representation of general logic programs should be abandoned in favor of graph representation of well-founded irreducible programs, which are more concise, more uniform in structure while being equally expressive.     

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。     

On the complexity of some inductive logic programming problems

The bounded ILP-consistency problem for function-free Horn clauses is described as follows. Given at setE ⁺ andE ^? of function-free ground Horn clauses and an integerk polynomial inE ⁺∪E ^?, does there exist a function-free Horn clauseC with no more thank literals such thatC subsumes each element inE ⁺ andC does not subsume any element inE ^?? It is shown that this problem is Σ ₂ ^P complete. We derive some related results on the complexity of ILP and discuss the usefulness of such complexity results.     

Visual Prolog的搜索控制机制分析

回溯机制是逻辑程序设计的重要设施。回溯本身是一种获得目标所有可能解的良好方法。然而回溯也有副作用,一是它可能导致Visual Prolog给出多余的答案,而Visual Prolog自己不能区分实质上相同的两个解,因此会降低效率;二是尽管一个特殊的目标已被满足,但是回溯机制可能还会强迫Visual Prolog继续手找另外的解,因此会增加系统开销。在这些情况下,必须仔细控制目标搜索求解的回溯过程。本文在揭示Visual Prolog回溯机制所存在问题的基础上,通过实例,对Visual Prolog的静态截断机制、失败谓词fail与否定谓词not等控制谓词,以及动态截断机制等所构成的完整的目标搜索求解控制机制进行了详细分析,从而揭示出回溯机制和搜索求解控制机制的本质特性及应用机理。     

String pattern-matching in Prolog

A pattern-matching feature for the Prolog language is described. Through the use of patterns, introduced as Prolog predicates, the feature favors the specification of string handling algorithms in a declarative style. A number of convenient pre-defined patterns, adapted from SNOBOL 4, are included. The use of two-level grammars as a paradigm for developing Prolog programs incorporating the pattern-matching feature is also discussed.     

Difference-list transformation for Prolog

Difference-lists are terms that represent lists. The use of difference-lists can speed up most list-processing programs considerably. Prolog programmers routinely use “difference-list versions” of programs, but very little investigation has taken place into difference-list transformation. Thus, to most programmers it is either unknown that the use of difference-lists is far from safe in all contexts, or else this fact is known but attributed to Prolog’s infamous “occur check problem.” In this paper we study the transformation of list-processing programs into programs that use differencelists. In particular we are concerned with finding circumstances under which the transformation is safe. We show that dataflow analysis can be used to determine whether the transformation is applicable to a given program, thereby allowing for automatic transformation. We prove that our transformation preserves strong operational equivalence. This paper is a revised and extended version of a paper¹⁰) that was presented to theInternational Computer Science Conference 88 in Hong Kong December 1988.     

Visual Prolog截断机制对回溯的作用机理

回溯是一种获得目标所有可能解的良好方法.然而不恰当地使用回溯,可能导致系统效率降低,时空开销增大,因此必须设置相应机制,仔细控制回溯过程.Visual Prolog的控制谓词,即失败谓词fail和否定谓词not,与截断机制,包括静态截断机制和动态截断机制,构成了完整的目标搜索求解控制机制,可以实现对搜索过程的仔细控制,减少不必要的回溯.该文在考察Visual Prolog回溯机制和截断机制的基础上,通过实例,对其静态截断机制和动态截断机制进行了详细分析,从而揭示回溯机制和截断机制的本质特性和应用机理.     

Towards a logic programming methodology based on higher-order predicates

This paper outlines a logic programming methodology which applies standardized logic program recursion forms afforded by a system of general purpose recursion schemes. The recursion schemes are conceived of as quasi higher-order predicates which accept predicate arguments, thereby representing parameterized program modules. This use of higher-order predicates is analogous to higher-order functionals in functional programming. However, these quasi higher-order predicates are handled by a metalogic programming technique within ordinary logic programming. Some of the proposed recursion operators are actualizations of mathematical induction principles (e.g. structural induction as generalization of primitive recursion). Others are heuristic schemes for commonly occurring recursive program forms. The intention is to handle all recursions in logic programs through the given repertoire of higher-order predicates. We carry out a pragmatic feasibility study of the proposed recursion operators with respect to the corpus of common textbook logic programs. This pragmatic investigation is accompanied with an analysis of the theoretical expressivity. The main theoretical results concerning computability are

1. Primitive recursive functions can be re-expressed in logic programming by predicates defined solely by non-recursive clauses augmented with afold recursion predicate akin to the fold operators in functional programming.
2. General recursive functions can be re-expressed likewise sincefold allows re-expression of alinrec recursion predicate facilitating linear, unbounded recursion.

     

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.