language: en

[To appear in Proceedings of the Second International Conference on AI Planning Systems (1994). Chicago: AAAI Press.]

Reactive and Automatic Behavior in Plan Execution

Pat Langley Wayne Iba Jeff Shrager
Robotics Laboratory Recom Technologies Palo Alto Research Center Computer Science Dept.
Mail Stop 269-2
Xerox Corporation Stanford University NASA Ames Research Center
3333 Coyote Hill Road Stanford, CA 94305 Moffett Field, CA 94035 Palo Alto, CA 94304
langley@cs.stanford.edu iba@wind.arc.nasa.gov shrager@xerox.com

Abstract Much of the work on execution assumes that the agent constantly senses the environment, which lets it respond immediately to errors or unexpected events. In this paper, we argue that this purely reactive strategy is only optimal if sensing is inexpensive, and we formulate a simple model of execution that incorporates the cost of sensing. We present an average-case analysis of this model, which shows that in domains with high sensing cost or low probability of error, a more `automatic' strategy - one with long intervals between sensing can lead to less expensive execution. The analysis also shows that the distance to the goal has no effect on the optimal sensing interval. These results run counter to the prevailing wisdom in the planning community, but they promise a more balanced approach to the interleaving of execution and sensing.

Reactive and Automatic Execution