Generalized Planning With Procedural Domain Control Knowledge

October 11, 2019 Β· Declared Dead Β· πŸ› International Conference on Automated Planning and Scheduling

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Authors Javier Segovia-Aguas, Sergio JimΓ©nez, Anders Jonsson arXiv ID 1910.04999 Category cs.AI: Artificial Intelligence Citations 36 Venue International Conference on Automated Planning and Scheduling Last Checked 4 months ago
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.
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