Book Review

Steve Minton's Learning Search Control Knowledge: An Explanation-Based Approach is the book form of his 1988 Ph.D. dissertation from CarnegieMellon University on learning control knowledge for planning. In particular, the work investigates the utility of learned knowledge for a planning system. This is an extremely important topic. Minton shows that knowledge, though correct and relevant, can degrade the planner's abilities when added. While demonstrated in the context of explanation-based learning, the effect encumbers inference systems in general. Indeed, it is well known that a certain artistry is required to design successful AI knowledge bases for nonlearning systems. It is not sufficient simply to cram all facts into a system; the cost ofsifting through a plethora of information to find the needed data can easily exceed the value of the answer. An explanation-based learning (EBL) system must come to grips with this artistic filtering of knowledge for which experienced AI knowledge engineers develop a sixth sense. At a time when the rest of the small-but-growing EBL community was worrying about how to learn, Steve Minton correctly anticipated the importance of when to learn. This shift is a landmark in the maturation of EBL as a scientific endeavor. While it is well known that the choice of problem representation and the