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Compiling Causal Theories to Successor State Axioms and STRIPS-Like Systems

机译:编制因果关系理论到后继状态公理和STRIPS-like系统

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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 non-monotonic 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.
机译:我们描述了一种用于指定动作效果的系统。与AI计划中常用的语言不同,我们的系统使用一种动作描述语言,该语言允许使用域规则来指定动作的效果,这是状态约束,可能会导致旧动作产生新的动作效果。可以断言,在我们的语言中,动作域对应于情境演算中的非单调因果理论。程序上,将这样一个动作域编译成一组逻辑理论,该逻辑理论用于该域中的每个动作,然后从中生成完全实例化的后继状态类公理和类STRIPS类系统。我们希望该系统成为知识工程师编写经典AI计划系统,GOLOG系统和其他需要正式操作规范的系统的操作规范的有用工具。

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