When to Plan and When to Act?

Faced with a complicated task, some initial planning can significantly increase the likelihood of success and increase efficiency, but planning for too long before starting to act can reduce efficiency. This paper explores the question of when to begin acting for a resource bounded agent. Limitations of an idealized algorithm suggested in the literature are presented and illustrated in the context of a robot courier. A revised, idealized algorithm is given and justified. The revised idealized algorithm is used as a basis for developing a new "step choice" algorithm for making on-the-fly decisions for a simplified version of the robot courier task. A set of experiments are used to illustrate the relative advantage of the new strategy over always act, always compute and anytime algorithm based strategies for deciding when to begin execution.