In this book the 0-approximation semantics is used to define regression in domains where an agent does not have complete information about the world, and may have sensing actions. The author started with domains having only Boolean fluents and formally related the definition of regression with the earlier definition of progression . Planning using such regression would not only give correct plans but also would not miss plans. A search algorithm for generating conditional plans was presented as an example application of the defined regression. Several heuristics and mutex computations were...