Planning domains often feature subproblems such as route planning and resource handling. Using static domain analysis techniques, we have been able to identify certain commonly occurring subproblems within planning domains, making it possible to abstract these subproblems from the overall goals of the planner and deploy specialized technology to handle them in a way integrated with the broader planning activities. Although such strategies can be impressive when applied to toy domains, they cannot address highly structured problem domains effectively. However, when knowledge-sparse approaches are supplemented by domain knowledge, they can perform impressively (Bacchus and Kabanza 2000) at the cost of an increased representation burden on the domain designer.

Planning domains often feature subproblems such as route planning and resource handling. Using static domain analysis techniques, we have been able to identify certain commonly occurring subproblems within planning domains, making it possible to abstract these subproblems from the overall goals of the planner and deploy specialized technology to handle them in a way integrated with the broader planning activities. Using two such subsolvers our hybrid planner, stan4, participated successfully in the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS'00) planning competition.