Generalized Planning With Procedural Domain Control Knowledge

TL;DR

This paper introduces a method for generating generalized plans using procedural domain control knowledge, enabling classical planners to efficiently solve diverse problems through callable procedures.

Contribution

It presents a divide and conquer approach to represent and compute generalized plans with procedural DCK, including nested and recursive calls, implemented in PDDL.

Findings

Classical planners can compute generalized plans using procedural DCK.

The approach handles complex domains like list sorting and binary tree traversal.

Procedural DCK improves planning efficiency and generalization.

Abstract

Generalized planning is the task of generating a single solution that is valid for a set of planning problems. In this paper we show how to represent and compute generalized plans using procedural Domain Control Knowledge (DCK). We define a {\it divide and conquer} approach that first generates the procedural DCK solving a set of planning problems representative of certain subtasks and then compile it as callable procedures of the overall generalized planning problem. Our procedure calling mechanism allows nested and recursive procedure calls and is implemented in PDDL so that classical planners can compute and exploit procedural DCK. Experiments show that an off-the-shelf classical planner, using procedural DCK as callable procedures, can compute generalized plans in a wide range of domains including non-trivial ones, such as sorting variable-size lists or DFS traversal of binary trees with variable size.