Is AI planning now?

ABSTRACT The current state of domain independent planning allows for a variety of levels of sophistication for describing world behavior and goals or objectives that the planner is to satisfy. Planners have become very efficient at searching the combinatorial spaces implicitly defined by these descriptions. On the results of the AIPS-98 planning competition, Yale University Professor and AIPS Planning Competition Chair, Drew McDermott states, "It is hard to draw any conclusion from these data, except to note that all of these planners performed very well, compared to the state of the art a few years ago. Many of the plans found were 30 or 40 steps long, and some were longer than 100 steps." [1, 10]