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Formalizing planning knowledge for hierarchical planning
Author(s) -
Yang Qiang
Publication year - 1990
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/j.1467-8640.1990.tb00126.x
Subject(s) - planner , computer science , preprocessor , automated planning and scheduling , set (abstract data type) , plan (archaeology) , feature (linguistics) , domain (mathematical analysis) , domain knowledge , process (computing) , artificial intelligence , mathematics , mathematical analysis , linguistics , philosophy , archaeology , history , programming language , operating system
A hierarchical planning system achieves efficiency by planning with the most important conditions first, and considering details later in the planning process. Few attempts have been made to formalize the structure of the planning knowledge for hierarchical planning. For a given domain, there is usually more than one way to define its planning knowledge. Some of the definitions can lead to efficient planning, while others may not. In this paper, we provide a set of restrictions which defines the relationships between a non‐primitive action and its set of subactions. When satisfied, these restrictions guarantee improved efficiency for hierarchical planning. One important feature of these restrictions is that they are syntactic and therefore do not depend on the particular structure of any plan. Along with these restrictions, we also provide algorithms for preprocessing the planning knowledge of a hierarchical planner. When used during planning, the preprocessed operator hierarchies can enable a planner to significantly reduce its search space.