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

TL;DR

This paper introduces a system that compiles causal theories into successor state axioms and STRIPS-like systems, enabling more expressive and formal action specifications for AI planning and related systems.

Contribution

It presents a novel method to specify action effects using domain rules and compiles them into logical theories and STRIPS-like systems, enhancing expressiveness and formalization.

Findings

System effectively encodes action effects with domain rules.

Generates successor state axioms from causal theories.

Facilitates formal action specifications for AI systems.

Abstract

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.