Abstract

Despite the long history of classical planning, there has been very little comparative analysis of the performance tradeoffs offered by the multitude of existing planning algorithms. This is partly due to the many different vocabularies within which planning algorithms are usually expressed. In this paper we show that refinement search provides a unifying framework within which various planning algorithms can be cast and compared. Specifically, we will develop refinement search semantics for planning, provide a generalized algorithm for refinement planning, and show that planners that search in the space of (partial) plans are specific instantiations of this algorithm. The different design choices in partial-order planning correspond to the different ways of instantiating the generalized algorithm. We will analyze how these choices affect the search space size and refinement cost of the resultant planner, and show that in …

Date

July 1, 1995

Authors

Subbarao Kambhampati, Craig A Knoblock, Qiang Yang

Journal

Artificial Intelligence

Volume

76

Issue

1-2

Pages

167-238

Publisher

Elsevier