ASPeRiX，一种用于答案集计算的一阶前向链接方法
ASPeRiX, a First Order Forward Chaining Approach for Answer Set Computing
摘要：
在人工智能中使用回答集编程（ASP）来表示知识或解决组合问题的自然方式是精心设计具有默认否定的一阶逻辑程序。在第一步中，这个带有变量的程序被第一个工具翻译成一个等价的命题：地球仪。然后，命题程序被交给第二个工具：求解器。最后一个计算（如果存在）程序的一个或多个答案集（稳定模型），每个答案集编码初始问题的一个解。直到今天，几乎所有的ASP系统都采用这两步计算。在这篇文章中，ASPeRiX项目是作为一个一阶前向链接方法的答案集计算。这个项目是第一个引入答案集计算方法的项目之一，该方法通过将其集成到搜索过程中来避免规则实例化的初始阶段。该方法适用于一阶规则的前向链接，这些规则通过先前产生的原子在飞行中接地。该方法的理论基础，ASP求解器ASPeRiX的主要算法进行了详细说明，并提供了一些实验和与现有系统的比较。
英文摘要：
The natural way to use Answer Set Programming (ASP) to represent knowledge in Artificial Intelligence or to solve a combinatorial problem is to elaborate a first order logic program with default negation. In a preliminary step this program with variables is translated in an equivalent propositional one by a first tool: the grounder. Then, the propositional program is given to a second tool: the solver. This last one computes (if they exist) one or many answer sets (stable models) of the program, each answer set encoding one solution of the initial problem. Until today, almost all ASP systems apply this two steps computation. In this article, the project ASPeRiX is presented as a first order forward chaining approach for Answer Set Computing. This project was amongst the first to introduce an approach of answer set computing that escapes the preliminary phase of rule instantiation by integrating it in the search process. The methodology applies a forward chaining of first order rules that are grounded on the fly by means of previously produced atoms. Theoretical foundations of the approach are presented, the main algorithms of the ASP solver ASPeRiX are detailed and some experiments and comparisons with existing systems are provided.
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。
