Utility-Directed Planning

Mike Williamson, Steve Hanks

Classical AI planning has adopted a very narrow notion of plan quality, namely that a plan is good just in case it achieves a specified goal. Goals provide a valuable point of computational leverage: despite the fact that planning is intractable in the worst case, goal-satisfying planning algorithms can effectively solve classes of problems by using the goal to focus the search for a solution (using backward-chaining techniques), and by exploiting domain-specific heuristic knowledge to control search.

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