This chapter has reviewed AI planning techniques as they apply in general. Process planning can involve some, or all of the techniques described here. The next chapter will discuss planning within the domain of manufacturing processes.
The reviewed planning literature makes it obvious that work needs to be done in planning. In particular, planners need to be developed that will deal with complex problems, that have process costs. It is the author’s opinion that as existing planners are applied to more applications, the existing planning techniques will be refined to meet the needs of the real world problems. A few features are listed below that would be desired in a planning system.
• Be able to deal with linear and non-linear plans.
• Produce a plan in a shorter time with a slightly higher cost.
• Produce plans with low costs, having greater computation time.
• Deal with plans involving millions of steps.
• Deal with equivalent operators.
• Be able to backtrack in the event of plan execution failures.
• Be able to perform inductive and deductive reasoning.
• Deal with probabilistic events.
The hierarchical planning approach has performed well on many of these points, suggesting that is an excellent method to consider for future planning research and application.