格蕴涵代数的软LI-理想

借助软集合,提出了格蕴涵代数的软LI-理想的概念,研究了软集运算下的一些诸如交、且等基本性质,并给出了格蕴涵代数的软LI-理想的一些等价刻画。此外,研究了格蕴涵代数的软LI-理想与格蕴涵代数的软格理想之间的关系。得到了格蕴涵代数的软LI-理想像与原像的性质。     

格蕴涵代数的软滤子

借助软集合,提出了格蕴涵代数的软滤子的概念,研究了其在软集运算下的一些基本性质,并给出了格蕴涵代数的软滤子的一些等价刻画。进一步,研究了格蕴涵代数的软滤子与格蕴涵代数的对偶软格理想之间的关系。得到了格蕴涵代数的软滤子像与原像的性质。     

基于嵌套语义的约束代数

1 引言约束数据库近期被Kanellakis等提出作为处理空间数据的一般性框架。约束数据库用约束来建模和检索数据。在数据层,约束能用有限的形式来表示可能是无限的关系元组集。例如,约束x~2 y~2≤9表示中心在点(0,0)处,半径为3的圆。在查询语言层,约束通过允许数学计算而增强了简单关系语言的表达能力,同时约束查询语言保留了关系查询语言的所有特征,如封闭性和自底向上求值。关系代数能被扩充来处理约束关系,这个新的代数叫做约束代数CALG。     

基于格结构的概念代数研究

近年来,概念格作为一种有效的概念分析、表示与应用模型,被越来越多的领域所应用。概念代数是在概念 格理论基础上提出的一种新的代数系统。目前,概念代数系统还只是雏形,很多方面的内容还需要扩展与进一步的研 究。基于格结构的概念代数研究分别对Nilsson概念代数、Wille概念代数和认知信息学中的概念代数的基本概念与 内容进行了介绍,对各方法进行了分析与比较,并证明Nilsson概念代数是一种广义概念代数,为进一步的应用与研 究提供支持。     

约束概念格的代数性质及其知识表示的完备性

约束概念格是一种依据用户对数据集的兴趣、认识等作为背景知识而构造的概念格结构。文中利用约束概念格结点之间的上下确界运算,构造约束概念格的代数系统,证明约束概念格的若干代数性质,以及知识表示的完备性,从而为约束概念格的应用奠定理论基础。     

软BCK代数

提出了软BCK代数的概念,研究了软BCK代数的并,交和乘积运算,讨论了这些运算的代数性质。     

软I-代数

将I-代数与软集相结合,提出了新概念软I-代数,并研究了它的基本代数性质,证明了两个软I-代数同构当且仅当它们的基础软集同构。     

软卷积代数

利用软集的概念定义了软卷积代数并研究它的基本代数性质,这一概念将卷积代数与关联代数统一到软卷积代数的概念下,为二者在决策学和密码学的应用起到桥梁作用。     

基于约束逻辑程序设计的排课算法研究

课程安排问题是典型的组合优化和不确定调度问题。采用约束逻辑程序设计的研究方法,结合课程安排自身的特点,通过约束推理找到最优的课程安排结果。约束逻辑程序设计综合了人工智能中一致性算法和启发式搜索算法,采用约束推理方法,能非常好地处理各种冲突,并且能快速地排出合理的课程。     

软集与软格

将Molodtsov于1999年提出的软集理论应用到格论中,提出了软格和软子格的概念,讨论了它们相关的性质。另外,基于[∈]-软集和q-软集的概念,讨论了理想软格和滤子软格的一些性质。     

Constraint Programming in Sweden

The authors survey the research and development in Sweden in constraint programming, which is rapidly becoming the method of choice for some kinds of constraint problems, such as scheduling and configuration.     

Stochastic Concurrent Constraint Programming

We present a stochastic version of Concurrent Constraint Programming (CCP), where we associate a rate to each basic instruction that interacts with the constraint store. We give an operational semantic that can be provided either with a discrete or a continuous model of time. The notion of observables is discussed, both for the discrete and the continuous version, and a connection between the two is given. Finally, a possible application for modeling biological networks is presented.     

Some Challenges for Constraint Programming

We propose a number of challenges for future constraint programming systems, including improvements in implementation technology (using global analysis based optimization and parallelism), debugging facilities, and the extension of the application domain to distributed, global programming. We also briefly discuss how we are exploring techniques to meet these challenges in the context of the development of the CIAO constraint logic programming system.     

Constraint Programming in Structural Bioinformatics

Bioinformatics aims at applying computer science methods to the wealth of data collected in a variety of experiments in life sciences (e.g. cell and molecular biology, biochemistry, medicine, etc.) in order to help analysing such data and eliciting new knowledge from it. In addition to string processing bioinformatics is often identified with machine learning used for mining the large banks of bio-data available in electronic format, namely in a number of web servers. Nevertheless, there are opportunities of applying other computational techniques in some bioinformatics applications. In this paper, we report the application of constraint programming to address two structural bioinformatics problems, protein structure prediction and protein interaction (docking). The efficient application of constraint programming requires innovative modelling of these problems, as well as the development of advanced propagation techniques (e.g. global reasoning and propagation), which were adopted in Chemera, a system that is currently used to support biochemists in their research.     

SC-PROLOG解释系统中的约束逻辑程序设计方法

约束逻辑程序设计（ＣＬＰ）方法是提高ＰＲＯＬＯＧ语言效率的一种崭新方法，本文针对ＳＣ┐ＰＲＯＬＯＧ解释系统的实现介绍其相应设计思想，从域变量含义入手，提出了域及约束的存储方法以及约束机制的实现算法，是对逻辑设计方法研究的一点体会     

约束归纳逻辑程序设计系统

提出了一种新的约束归纳逻辑程序设计方法，并初步实现了一个自顶向下的约束归纳逻辑程序原型系统。该系统能够导出不受变量个数限制的多种形式的线性约束，得出覆盖正例而排斥负例的含约束的Hom子句程序。     

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.     

约束编程与约束满足在产品装配中的应用

约束编程与约束满足问题是近三十年来在人工智能领域发展起来的一个研究方向。产品配置器近十几年来发展起来的一项技术。文中介绍约束编程及约束满足问题在按订单装配型产品配置器中的应用，并通过讨论说明了相对于传统配置方案求解过程，应用约束满足的优越性。