Stochastic Constraint Programming: A Scenario-Based Approach

To model combinatorial decision problems involving uncertainty and probability, we introduce scenario based stochastic constraint programming. Stochastic constraint programs contain both decision variables, which we can set, and stochastic variables, which follow a discrete probability distribution. We provide a semantics for stochastic constraint programs based on scenario trees. Using this semantics, we can compile stochastic constraint programs down into conventional (non-stochastic) constraint programs. This allows us to exploit the full power of existing constraint solvers. We have implemented this framework for decision making under uncertainty in stochastic OPL, a language which is based on the OPL constraint modelling language [Van Hentenryck et al., 1999]. To illustrate the potential of this framework, we model a wide range of problems in areas as diverse as portfolio diversification, agricultural planning and production/inventory management.     

PSICO: Solving Protein Structures with Constraint Programming and Optimization

In this paper we propose PSICO (Processing Structural Information with Constraint programming and Optimisation) as a constraint-based approach to determining protein structures compatible with distance constraints obtained from Nuclear Magnetic Resonance (NMR) data. We compare the performance of our proposed algorithm with DYANA (Dynamics algorithm for NMR applications) an existing commercial application based on simulated annealing. On a test case with experimental data on the dimeric protein Desulforedoxin, the method proposed here supplied similar results in less than 10 minutes compared to approximately 10 hours of computation time for DYANA. Although the quality of results can still be improved, this shows that CP technology can greatly reduce computation time, a major advantage because structural NMR technique generally demands multiple runs of structural computation.     

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。     

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。     

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.     

约束逻辑编程中宽数据算术运算算法

提出了一种在利用约束逻辑编程生成RTL数据通路模拟矢量的方法中处理宽数据的新方法。该方法解决了现有CLP求解器所能处理的最大整数限制问题。该文设计并实现了宽数据加法、减法和乘法运算的分解算法，运算分解扩展了现有CLP的功能，使其能适应实际的数据通路设计。实验结果表明方法是有效的。     

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.     

Models for Global Constraint Applications

In this paper we give an overview of some industrial applications built using global constraints. We look at three systems from different application domains and show the core models used to express their constraints. We also consider different search strategies that have been applied and discuss some of the application aspects.     

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。     

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.     

基于结构约束生成对抗网络的书法汉字生成

目前书法汉字的生成研究在汉字生成过程中需要大量先验汉字组成信息,不仅对前期数据收集工作的要求较高,而且影响研究成果的扩展性.针对此问题,文中提出基于结构约束的条件堆叠生成对抗网络的书法汉字生成方法.将源汉字图像直接提取的汉字笔迹作为结构约束条件,通过条件堆叠生成对抗网络模型生成高质量的书法汉字.同时提出通过伪目标样本的...     

逻辑程序在关系数据库完整性约束中的应用

逻辑程序设计语言具有很强的逻辑推理能力,将逻辑程序规则与数据库耦合在一起,可以扩充原有的关系数据库完整性约束规则.本文初步探讨了用逻辑程序实现关系数据库完整性约束的实现方法,该方法可以解决语义上逻辑错误的约束.     

适应性结构保持约束下的目标跟踪方法?

针对目标在运动过程中的结构保持特性,提出一种目标结构化外观描述方法。该方法构建区域节点反映目标局部特性,定义区域节点的软/硬结构约束,将目标的局部特性、全局特性及区域节点的空间结构关系统一于目标的结构化描述中。通过匹配帧间局部区域的尺度不变特征转换流,粗略估计目标运动状态,并利用区域节点的软/硬结构约束对跟踪结果进行约束调整,称为适应性结构保持。公测视频序列的实验表明,相比已有方法,文中方法能更有效跟踪形变、阴影与光照变化下的目标,对目标与背景相似和视频低分辨率等情况也有较高的跟踪性能,具有强鲁棒性和一定的泛化能力。     

Stochastic Concurrent Constraint Programming and Differential Equations

We tackle the problem of relating models of systems (mainly biological systems) based on stochastic process algebras (SPA) with models based on differential equations. We define a syntactic procedure that translates programs written in stochastic Concurrent Constraint Programming (sCCP) into a set of Ordinary Differential Equations (ODE), and also the inverse procedure translating ODE's into sCCP programs. For the class of biochemical reactions, we show that the translation is correct w.r.t. the intended rate semantics of the models. Finally, we show that the translation does not generally preserve the dynamical behavior, giving a list of open research problems in this direction.     

Constraint satisfaction with an object-oriented knowledge representation language

This article gives a detailed presentation of constraint satisfaction in the hybrid LAURE language. LAURE is an object-oriented language for Artificial Intelligence (AI) applications that allows the user to combine rules, constraints, and methods that cooperate on the same objects in the same program. We illustrate why this extensibility is necessary to solve some large and difficult problems by presenting a real-life application of LAURE. We describe the syntax and the various modes in which constraints may be used, as well as the tools that are proposed by LAURE to extend constraint resolution. The resolution strategy as well as some implementation details are given to explain how we obtain good performances.     

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。     

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     

约束求解与优化技术的结合

提出了将混合约束问题转化为混合整数规划问题的方法.用约束求解方法及混合整数规划方法共同求解混合约束问题可以令二者相互借鉴,从而促进二者求解技术的进一步发展.同时,由混合约束问题转化而来的混合整数规划问题也可作为求解混合整数规划问题的测试问题（benchmarks）.     

A Constraint-Based Approach to Fast and Exact Structure Prediction in Three-Dimensional Protein Models

Simplified protein models are used for investigating general properties of proteins and principles of protein folding. Furthermore, they are suited for hierarchical approaches to protein structure prediction. A well known protein model is the HP-model of Lau and Dill [Lau, K. F., & Dill, K. A. (1989)]. A lattice statistical mechanics model of the conformational and sequence spaces of proteins. Macromolecules, 22, 3986–3997) which models the important aspect of hydrophobicity. One can define the HP-model for various lattices, among them two-dimensional and three-dimensional ones. Here, we investigate the three-dimensional case. The main motivation for studying simplified protein models is to be able to predict model structures much more quickly and more accurately than is possible for real proteins. However, up to now there was a dilemma: the algorithmically tractable, simple protein models can not model real protein structures with good quality and introduce strong artifacts. We present a constraint-based method that largely improves this situation. It outperforms all existing approaches for lattice protein folding in HP-models. This approach is the first one that can be applied to two three-dimensional lattices, namely the cubic lattice and the face-centered-cubic (FCC) lattice. Moreover, it is the only exact method for the FCC lattice. The ability to use the FCC lattice is a significant improvement over the cubic lattice. The key to our approach is the ability to compute maximally compact sets of points (used as hydrophobic cores), which we accomplish for the first time for the FCC lattice.