将因果理论编译为后继状态公理和类STRIP系统
Compiling Causal Theories to Successor State Axioms and STRIPS-Like Systems
摘要：
我们描述了一个系统指定的行动的影响。与人工智能规划中常用的那些不同，我们的系统使用一种动作描述语言，允许人们使用域规则来指定动作的效果，域规则是状态约束，可以从旧的动作中产生新的动作效果。声明，在我们的语言中的行动域对应于一个非单调的因果理论的情况演算。在程序上，这样的动作域被编译成一组逻辑理论，一个用于域中的每个动作，然后生成完全实例化的后继状态类公理和类STRIPS系统。我们希望该系统是一个有用的工具，知识工程师编写经典的人工智能规划系统，GOCNET系统，和其他系统的行动需要正式规范的行动规范。
英文摘要：
We describe a system for specifying the effects of actions. Unlike those commonly used in AI planning, our system uses an action description language that allows one to specify the effects of actions using domain rules, which are state constraints that can entail new action effects from old ones. Declaratively, an action domain in our language corresponds to a nonmonotonic causal theory in the situation calculus. Procedurally, such an action domain is compiled into a set of logical theories, one for each action in the domain, from which fully instantiated successor state-like axioms and STRIPS-like systems are then generated. We expect the system to be a useful tool for knowledge engineers writing action specifications for classical AI planning systems, GOLOG systems, and other systems where formal specifications of actions are needed.
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。
