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arXiv cs/0506005cs.PL
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在动作规则中实现单域约束条件

Programming Finite-Domain Constraint Propagators in Action Rules

Neng-Fa Zhou

摘要:

在本文中,我们提出了一种新的语言,称为AR({ \it Action Rules}),并描述了各种传播有限域的约束可以在其中实现。一个动作规则指定一个模式的代理,代理可以执行的动作,和事件模式的事件,可以激活代理。AR将逻辑编程的面向目标的执行模型与事件驱动的执行模型相结合。这种混合执行模型有利于编程约束传播。约束的传播子是一个代理,它维护约束的一致性,并由约束中的域变量的更新激活。AR具有比目前有限域约束系统中广泛使用的语言{ \it indexicals}更强的描述能力,并且不仅可以灵活地实现区间一致性算法,还可以实现弧一致性算法。作为例子,我们提出了一个弱弧一致性传播的{ \tt all\_distinct}约束和混合算法的n元线性等式约束。B-Prolog已经扩展以适应动作规则。基准测试表明,B-Prolog作为一个CLP(FD)系统显着优于其他CLP(FD)系统。

英文摘要:

In this paper, we propose a new language, called AR ({\it Action Rules}), and describe how various propagators for finite-domain constraints can be implemented in it. An action rule specifies a pattern for agents, an action that the agents can carry out, and an event pattern for events that can activate the agents. AR combines the goal-oriented execution model of logic programming with the event-driven execution model. This hybrid execution model facilitates programming constraint propagators. A propagator for a constraint is an agent that maintains the consistency of the constraint and is activated by the updates of the domain variables in the constraint. AR has a much stronger descriptive power than {\it indexicals}, the language widely used in the current finite-domain constraint systems, and is flexible for implementing not only interval-consistency but also arc-consistency algorithms. As examples, we present a weak arc-consistency propagator for the {\tt all\_distinct} constraint and a hybrid algorithm for n-ary linear equality constraints. B-Prolog has been extended to accommodate action rules. Benchmarking shows that B-Prolog as a CLP(FD) system significantly outperforms other CLP(FD) systems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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