Preface

Classical planning has made huge advances in the last twenty years, leading to solvers able to create plans with thousands of actions for problems described by hundreds of propositions. Yet, the assumptions of classical planning (determinism, model completeness, etc) are oen criticised as being too restrictive to address "real" planning problems. Recently, however, many researchers have started to exploit the good performance of classical planners, through compilations and other methods of reuse, to solve a much wider range of problems. In this way, classical planners have been used for dealing with more expressive planning problems, including incomplete information, temporally extended goals and preferences, as well as to solve problems in various areas of application. Likewise, approaches range from pure compilation (translating a problem into PDDL and solving it with a classical planner) to embedding classical planning techniques inside dedicated algorithms. is body of contributions help illustrate how the results of decades of research in classical planning are now being put to use.