This section can be considered transitional in many ways. The main concern so far with motion planning has been feasibility as opposed to optimality. This placed the focus on finding any solution, rather than further requiring that a solution be optimal. In later parts of the book, especially as uncertainty is introduced, optimality will receive more attention. Even the most basic forms of decision theory (the topic of Chapter 9) center on making optimal choices. The requirement of optimality in very general settings usually requires an exhaustive search over the state space, which amounts to computing continuous cost-to-go functions. Once such functions are known, a feedback plan is obtained, which is much more powerful than having only a path. Thus, optimality also appears frequently in the design of feedback plans because it sometimes comes at no additional cost. This will become clearer in Chapter 8. The quest for optimal solutions also raises interesting issues about how to approximate a continuous problem as a discrete problem. The interplay between time discretization and space discretization becomes very important in relating continuous and discrete planning problems.