Planning and Meta-Planning (MOLGEN: Part 2)

The selection of what to do next is often the hardest part of resource-limited problem solving. In planning problems, there are typically many goals to be achieved in some order. The goals interact with each other in ways which depend both on the order in which they are achieved and on the particular operators which are used to achieve them. A planning program needs to keep its options open because decisions about one part of a plan are likely to have consequences for another part. This paper describes an approach to planning which integrates and extends two strategies termed the least-commitment and the heuristic strategies. By integrating these, the approach makes sense of the need for guessing; it resorts to plausible reasoning to compensate for the limitations of its knowledge base. The decision-making knowledge is organized in a layered control structure which separates decisions about the planning problem from decisions about the planning process. The approach, termed meta-planning, exposes and organizes a variety of decisions, which are usually made implicitly and sub-optimally in planning programs with rigid control structures. This is part of a course of research which seeks to enhance the power of a problem solvers by enabling them to reason about their own reasoning processes. Meta-planning has been implemented and exercised in a knowledge-based program (named MOLGEN) that plans gene cloning experiments in molecular genetics.