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首页> 外文期刊>Journal of Intelligent Information Systems >A Deductive Database Approach to A.I. Planning
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A Deductive Database Approach to A.I. Planning

机译：人工智能的演绎数据库方法规划

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摘要

In this paper, we show that the classical A.I. planning problem can be modelled using simple database constructs with logic-based semantics. The approach is similar to that used to model updates and nondetermin-ism in active database rules. We begin by showing that planning problems can be automatically converted to Datalog_(1 S) programs with nondeterministic choice constructs, for which we provide a formal semantics using the concept of stable models. The resulting programs are characterized by a syntactic structure (XY-stratification) that makes them amenable to efficient implementation using compilation and fixpoint computation techniques developed for deductive database systems. We first develop the approach for sequential plans, and then we illustrate its flexibility and expressiveness by formalizing a model for parallel plans, where several actions can be executed simultaneously. The characterization of parallel plans as partially ordered plans allows us to develop (parallel) versions of partially ordered plans that can often be executed faster than the original partially ordered plans.
机译：在本文中，我们展示了经典的人工智能可以使用具有基于逻辑的语义的简单数据库构造对计划问题进行建模。该方法类似于用于对活动数据库规则中的更新和不确定性进行建模的方法。我们首先显示可以使用非确定性选择结构将计划问题自动转换为Datalog_（1 S）程序，为此我们使用稳定模型的概念提供了形式语义。生成的程序具有语法结构（XY分层）的特征，使其可以使用为演绎数据库系统开发的编译和定点计算技术进行有效实施。我们首先开发用于顺序计划的方法，然后通过形式化并行计划的模型来说明其灵活性和表达力，该模型可以同时执行多个动作。将并行计划表征为部分有序计划，使我们能够开发（并行）部分有序计划，这些版本通常比原始部分有序计划执行得更快。

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