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 subplan, 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.

Many potential real-world planning applications are on the border of planning and scheduling. To handle the complex choices of actions and temporal and resource constraints of these problems we need to integrate planning and scheduling techniques. Here we propose a transition-based formulation of temporal planning problems, that enables us to represent features like deadlines, time windows, release times etc. in a simple way. We describe a CSP encoding of the transition-based formulation and its potential advantages in integrating planning and scheduling techniques.