约束程序设计语言COPS的设计与实现

约束程序设计作为面向智能应用的实用型程序设计风格正在AI领域产生越来越大的影响，其关键问题是如何将说明性的知识表示、系统化和启发式的推理搜索能力以及合理的确定性计算开销统一起来。该文介绍了设计实现的并发约束程序设计语言COPS。COPS系统的主要目标是探索智能语言的实用化与工程化，使其能够真正解决现实世界中用常规语言难以实现的智能应用问题。还介绍了COPS语言的表示及涉及的主要推理技术。     

约束逻辑程序设计综述

一、引言 约束逻辑程序设计(Constraint Logic Program-ming．CLP)是基于人工智能(AI)中约束满足问题(Constraint Satisfaction Problem．CSP)模型的一种程序设计风范。CLP是逻辑程序设计(LP)的一种推广,是八十年代发展起来的一种新的逻辑程序设计方法。由于它继承了LP简单易懂的说明性描述方法并结合了CSP在求解问题时的效率,使它在解决很多AI问题(如组合问题、资源分配、事务安排等)时有不凡的表现。更由于AI领域中绝大多数问题可以用CLP来表示,所以这一方法已引起了人们的广泛注意,并在八十年代后期得以迅速发展。     

带迭代算子的函数式程序设计

本文提出了程序设计语言的一种新的计算模型，带迭代处子的函数式模型，文中给出了基于该计算模型的程序设计语言的语法、计算规则集及确定怀证明，该类语言以表达式的复合描述顺序，以迭代表达式描述循环，以条件表达式描述分支，使得程序以数学语义为基础，易于理解，证明及构造高效的执行系统，相信该类语言是一咱有坚实理论基础、高效的、实际有用的高级确定性程序设计语言。     

逻辑程序设计语言G(o)del与Prolog的比较

在多态多类的一阶逻辑基础之上,围绕类型系统、模块系统、控制机制、元程序设计和输入／输出部分对Gǒdel语言功能进行分析。重点比较了逻辑程序设计语言Gǒdel与Prolog的联系与区别,通过比较分析,表明由于摒弃了Prolog语言中的非逻辑成分,引入了多种新的语言成分,Gǒdel语言具有更好的说明性语义和执行效率。     

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。     

逻辑语言剪枝算子的过程语义及其实现

论述了逻辑程序设计中剪枝算子的作用及传统剪枝算子的过程性语义和说明性语义不一致问题;介绍了新型逻辑程序语言〔淑划中的COTRTT11t剪枝算子;通过引入一组定义描述其过程语义,并进一步阐述了剪枝算子和延迟计算规则之间的关系,讨论了Godel语言的剪枝策略及控制机制,从而为逻辑程序语言的实现提供了依据。     

一个并发对象演算

由于缺乏一个为人们接受的描述并发对象系统语义的形式化模型,开发面向对象程序设计语言的开发受到了很大的制约,为了给并发面向对象程序设计定义一个公共的语义框架,人们分别以π演算和ａｃｔｏｒ模型为基础进行了研究。     

面向对象的约束逻辑程序设计

本文介绍了面向对象技术和约束逻辑程序设计方法在人工智能中应用的基本思想，通过二者的结合使现有逻辑程序设计在逻辑的清晰性和执行的高效性上都得以提高，这样就引入了一个新的研究方向：面向对象的约束逻辑程序设计     

逻辑程序的语义问题(Ⅰ)

说明性语义是逻辑程序研究的重要内容,也是其作为说明性程序的基本特征。近年来由于人们对带否定前提的一般逻辑程序设计的关注,以及逻辑程序与非单调推理的结合,逻辑程序的语义研究出现了许多新结果。本文以早期的Clark语义和最小模型语义为起点,介绍这些新发展的部分内容,主要包括Clark语义的Fitting 3-值扩充,理想模型语义、稳定模型语义、良基模型语义以及它们之间的关系,并在此基研上进一步讨论了说明性语义在逻辑程序设计中的地位和作用。     

并发产生式系统COPS通讯原语的设计

COPS(Concurrent Official Production System)是将产生式系统程序设计语言OPS5和面向进程的程序设计范例相结合,而设计的用于支持协同式问题求解的程序系统。本文详细阐述了COPS通讯原语的设计及其对应的语法和语义。COPS不仅能在单机上实现,而且也可以直接的移植到分布式系统上。     

Communicating sequential processes for distributed constraint satisfaction

CSPCONS is a programming language that supports program execution over multiple Prolog processes with constraints. The language is an extended version of Csp-ii, a version of Prolog that supports channel-based communicating processes and TCP/IP communication, that is based on the CSP model introduced by Hoare. Cspcons inherits all the advanced features of Csp-ii and extends it by introducing constraint solving capabilities to the processes. In Cspcons each Prolog process has one or more solvers attached and each solver is independent from the others, following the original Csp-ii model, thus resulting to a communicating sequential constraint logic programming system. Such a model can facilitate greatly the implementation of distributed CLP applications. This paper describes the original Csp-ii system along with details of the extensions that resulted to the Cspcons system and presents an example demonstrating the applicability of the system to distributed constraint satisfaction problems.     

HIERARCHICAL ARC CONSISTENCY FOR DISJOINT REAL INTERVALS IN CONSTRAINT LOGIC PROGRAMMING

There have been many proposals for adding sound implementations of numeric processing to Prolog. This paper describes an approach to numeric constraint processing which has been implemented in Echidna, a new constraint logic programming (CLP) language. Echidna uses consistency algorithms which can actively process a wider variety of numeric constraints than most other CLP systems, including constraints containing some common nonlinear functions. A unique feature of Echidna is that it implements domains for real-valued variables with hierarchical data structures and exploits this structure using a hierarchical arc consistency algorithm specialized for numeric constraints. This gives Echidna two advantages over other systems. First, the union of disjoint intervals can be represented directly. Other approaches require trying each disjoint interval in turn during backtrack search. Second, the hierarchical structure facilitates varying the precision of constraint processing. Consequently, it is possible to implement more effective constraint processing control algorithms which avoid unnecessary detailed domain analysis. These advantages distinguish Echidna from other CLP systems for numeric constraint processing.     

Nicolog: A simple yet powerful cc(FD) language

In this paper, we describe Nicolog, a language with capabilities similar to recently developed constraint logic programming (CLP) languages such as CLP(BNR), clp(FD), and cc(FD). Central to Nicolog are projection constraints (PCs), a sublanguage for compiling and optimizing constraint propagation in numeric and Boolean domains. PCs are an interesting generalization of the indexical constraints introduced in cc(FD) and also found in clp(FD). Nicolog compiles a very general class of built-in constraints into equivalent sets of PCs, allowing an arbitrary mixture of integer (easily extensible to real) and Boolean operations. Nicolog also lets the user program PCs directly, making it possible to implement new sophisticated propagation procedures. We show that PCs are a simple, efficient, and flexible way to implement most of the propagation procedures possible in other FD CLP systems. These include procedures for cardinality, constructive disjunction, implication, and mixed Boolean/numeric constraints. Empirical results with a simple prototype Nicolog implementation based on the WAM architecture show it can solve hard problems with speed comparable to the fastest existing CLP systems.     

Constraint Retraction in CLP(FD): Formal Framework and Performance Results

Constraint retraction can be described, in general, as the possibility of deleting a previously stated piece of information. This is obviously very convenient in many programming frameworks, especially in those that involve some level of interaction between the user and the system, or also in those concerning rescheduling or replanning. Nevertheless, constraint retraction is usually not provided in current constraint programming environments. This is mainly due to its high complexity and also to its non-monotonic nature, which would make most of such systems much more complex to reason with. In this paper we avoid these problems by considering a specific constraint programming framework, called clpFD, that is, constraint logic programming (CLP) over finite domain (FD) constraints. We propose an algorithm which deletes a constraint from a set of FD constraints, while maintaining partial arc-consistency, which is usual in this programming framework. What is crucial is that the retraction operation we propose is incremental, in that it follows the chain of dependencies among variables which are set by the nature of the FD constraints, and by doing so it updates only the part of the constraint set which is affected by the deletion. We also detail how constraint retraction can be incorporated in the FD constraint solver and we evaluate its behavior within the clpFD system. Experimental results on usual benchmarks, on classes of problems of increasing connectivity, and also on a real-life problem show that in almost all cases the use of our retraction algorithm provides great speed-up with respect to standard methods while not slowing down the clpFD system when no retraction is performed. This provides the system with an efficient way of retracting constraints while not changing its performance when the user does not want to use this new feature.     

基于电子信息专业的“C语言程序设计”探讨

目前,基于电子信息专业的“C语言程序设计”研究已较为深入,在培养电子信息专业人才方面也设立了相应方案。文章探讨了基于电子信息专业的“C语言程序设计”教学现状,提出具体的专业“C语言程序设计”教学思路,并就具体的教学改革策略进行了全盘分析,探讨。     

RTL数据通路模拟矢量自动生成方法研究与实现

针对已有的RTL数据通路模拟矢量自动生成方法的不足，提出一种利用约束逻辑编辑(CLP)自动生成数据通路模拟矢量的新方法．该方法首先对给定的Verilog RTL描述采用程序切片进行设计化简，然后对化简后的结果基于位向量算术原理生成CLP约束，并利用CLP求解器GProlog进行约束求解，最终生成满足输出要求的模拟矢量．该方法约束求解速度快，生成的约束是统一的，得到的模拟矢量较完备，能满足模拟验证的要求．实验结果表明，文中方法是一种高效的RTL数据通路模拟矢量自动生成方法．     

A pure proactive scheduling algorithm for multiple earth observation satellites under uncertainties of clouds

Most earth observation satellites (EOSs) are equipped with optical sensors, which cannot see through clouds. Hence, observations are significantly affected and blocked by clouds. In this work, with the inspiration of the notion of a forbidden sequence, we propose a novel assignment formulation for EOS scheduling. Considering the uncertainties of clouds, we formulate the cloud coverage for observations as stochastic events, and extend the assignment formulation to a chance constraint programming (CCP) model. To solve the problem, we suggest a sample approximation (SA) method, which transforms the CCP model into an integer linear programming (ILP) model. Subsequently, a branch and cut (B&C) algorithm based on lazy constraint generation is developed to solve the ILP model. Finally, we conduct a lot of simulation experiments to verify the effectiveness and efficiency of our proposed formulation and algorithm.     

CLPGUI: A Generic Graphical User Interface for Constraint Logic Programming

CLPGUI is a generic graphical user interface for visualizing and controlling the execution of constraint logic programs. CLPGUI has been designed to be used in different contexts: initially for teaching purposes, then for debugging complex programs of real-world scale, and recently for developing end-user interfaces. The challenge of developing a tool which is generic w.r.t. both the constraint logic programming system and the visualizers, is addressed by a client-server architecture for connecting a CLP process to a Java-based GUI process, and by a non-intrusive tracing and control method based on annotations in the CLP program. Arbitrary constraints and goals can be posted incrementally from the GUI in an interactive manner, and arbitrary states can be recomputed. We describe several generic 2D and 3D viewers of the variables and of the search tree, and argue that the 3D representation is best-suited to apprehend the shape of large search trees. We also illustrate the use of CLPGUI for developing application-oriented end-user interfaces on two placement problems, one in virtual reality.     

以“数据结构”课程为导向的“C语言程序设计”课程的教学研究与实施

以“数据结构”课程为导向,可以指导“C语言程序设计”课程相关内容的应用案例设计。而将“以赛促学”的思想融入计算机大类基础课程中,以成果为导向,分层次学习“C语言程序设计”和“数据结构”,循序渐进,并针对每个知识点的项目案例驱动学习兴趣,可以体现应用型本科学以致用的宗旨。