W e designed the Simple Hierarchical Ordered Planner (SHOP) and its successor, SHOP2, with two goals in mind: to investigate research issues in automated planning and to provide some simple, practical planning tools. SHOP and SHOP2 are based on a planning formalism called hierarchical task network planning, which is described in more detail in the sidebar, "Automated and HTN Planning," on pages 36-37. Most automated planning systems do a trial-anderror search of a large space of possible

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... ns, and the planner might have to try many different possibilities before finding a plan that works. HTN planners perform this search by applying HTN methods, which are essentially forms that describe how to decompose tasks into subtasks. HTN methods generally describe the "standard operating procedures" normally used to perform tasks in some domain; thus, they often correspond well to how users think about problems. In any trial-and-error search, one of the most important questions is what kind of search-control strategy to use. Unlike most other HTN planners, SHOP and SHOP2 use a search-control strategy called ordered task decomposition, which breaks tasks into subtasks and generates the plan's actions in the same order that the plan executor will execute them. So, throughout the planning process, the planner can tell what the state of the world will be at each step of the plan. To produce the decomposition tree in Figure 1a , for example, SHOP2 would decompose the tasks in the order t 1 , t 2 , t 3 , t 4 , t 5 , t 6 , t 7 , t 8 , t 9 , t 10 , and to produce the decomposition tree in Figure 1b , SHOP2 would decompose the tasks in the order t 1 , t 2 , t 6 , t 7 , t 3 , t 4 , t 5 , t 8 , t 9 , t 10 . SHOP is similar to SHOP2, but it requires a strict P l a n n i n g w i t h T e m p l a t e s EXECUTIVE COMMITTEE President: