Will Briggs, Lynchburg College and Diane J. Cook, University of Texas at Arlington
Anytime algorithms are useful when the time available for computation is limited, that is, when there is a tradeoff between the time cost of further computation and the cost of using a solution that is only partially complete. Although machine planning presents this sort of problem, there has not yet been a treatment of anytime planning for the general case, that is, a treatment not tied to specific domains. In this paper, we present a model for general-purpose anytime planning which allows the user to trade off the optimality of plans generated deliberatively with the speed of reactive plan generation. The anytime planner allows an interruption of hierarchical deliberative planning at the completion of any criticality level, and completes the plan at execution time using reactive planning. We illustrate the usefulness of this approach on a manufacturing domain.