Myers, L. and Smith, S. and Hildum, D. and Jarvis, P. and de Lacaze, R. Integrating Planning and Scheduling through Adaptation of Resource Intensity Estimates. Proceedings of the 6th European Conference on Planning (ECP-01), 2001.
Abstract
We describe an incremental and adaptive approach to integrating hierarchical task network planning and constraint-based scheduling. The approach is grounded in the concept of approximating the ‘resource intensity’ of planning options. A given planning problem is decomposed into a sequence of (not necessarily independent) subtasks, which are planned and then scheduled in turn. During planning, operators are rated according to a heuristic estimate of their expected resource requirements. Options are selected that best match a computed ‘target intensity’ for planning. Feedback from the scheduler is used to adapt the target intensity after completion of each sub-plan, thus guiding the planner toward solutions that are tuned to resource availability. Experimental results from an air operations domain validate the effectiveness of the approach relative to typical “waterfall” models of planner/scheduler integration.
Keywords: Artificial Intelligence, Artificial Intelligence Center, AIC
