IBAC~WIND.ARC.NASA.GOV

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 pa-per, we argue that this purely reactive strategy is only optimal if sensing is inexpensive, and wc formulate a sim-ple model of execution that incorporates the cost of sens-ing. 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 inter~als between sensing- can lead to less expensive execution. The analysis also shows that the distance to the goal has no effect on the optimal sens-ing 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 Much of the recent research on plan execution and control has focused on reactive systems. Onc central characteristic of such approaches is that the agent senses the environment on each time step, thus ensuring that it can react promptly to any errors or othcr unexpected events. This holds whether the agent draws on large-scale knowledge structures, such as plans (Howe & Co-hen, 1991)or cases (Hammond, Converse, & Marks, 1988), or bases its decisions on localized structures, suc