An operator induction tool supporting knowledge engineering in planning

Within the eld of arti cial intelligence are many disciplines, one of which is planning. Planning seeks to nd a suitable sequence of actions to carry out a task speci ed as a set of initial states for the objects involved in the actions and a required goal state. To do this the system has to have enough knowledge about the `world' in the form of a planning domain model. The process of constructing a planning domain model requires knowledge engineering. The structuring of the knowledge is important and hand-coding a domain model is a tedious and error-prone process. Static knowledge in the domain requires little update but the same cannot be said for the dynamic knowledge. The most di cult area of engineering planning domain models is the acquisition of operator schema, which contain descriptions of all the primitive actions (operators). In hierarchical models where actions may be modelled as sub-tasks, construction of these actions (methods) is particularly di cult and error-prone. We argue for a system whereby dynamic knowledge can be generated for every planning eventuality. The major contribution of the thesis is a method for inducing primitive and hierarchical actions from several solution examples, without the bene t of intermediate state information. In our system, opmaker , actions are generated from relatively short action sequences, indicated by a user, who has simply to name an action and identify associated objects as being a ected or una ected by the action. To complete a planning task the system uses the static domain knowledge, the initial and goal states from the planning task, and the action sequences. Using these it rst deduces possible state-change pathways which, using the right heuristics, may be unique (or at most have only a handful of pathways), and uses these to induce all the actions it needs. These actions can then be learned or regenerated at will. x We show that these induced actions compare to hand-crafted versions and can be used in planning. We can demonstrate that the hierarchical methods o er greater e ciency in planning times when compared to domains where previously no methods were o ered. The motivation for these ideas comes from the need to extend the development of GIPO, an integrated package for the construction of domain models in the form of a graphical user interface. We show how opmaker1 has already become a tool within GIPO for at domains and argue for the inclusion of its successor, opmaker2. Descriptions of domain construction and results using opmaker with several example domains are given. We analyse how, in general, this work contributes to and supports knowledge within the eld, and the thesis concludes with suggestions for future work and discusses the particular contributions o ered by opmaker to planning and knowledge engineering. xi ACKNOWLEDGEMENTS I would particularly like to thank my supervisor, Lee McCluskey, for his advice encouragement and `pep' talks when the going got rough during my time as a PhD student. I am indebted to Lee for his constructive advice on the content of this thesis and for always being able to see the `bigger picture'. To Margaret West I would like to extend my gratitude for all the patient hours helping me with Prolog and keeping me on track. I would also like to thank both my second supervisors, Margaret West and Diane Kitchin, for their advice on the readability of this thesis. My thanks also go to Stephen Cresswell who has been invaluable for the discussion of ideas, arguing about invariants and algorithms, and sharing the excitement of good results with cautious optimism. I would like to express my thanks to my family for their unstinting support of this venture, for their encouragement and belief in me and, in the case of my husband Mike, for his sheer determination when I had lost mine! Finally I would like to dedicate this thesis to my father, Frank Douthwaite, who sadly died six months before its completion, but who would have been proud to see his daughter succeed. xii DECLARATION I grant powers of discretion to the University Librarian to allow this thesis to be copied in whole or in part without further reference to me. This permission covers only single copies made for study purposes, subject to normal conditions of acknowledgement. xiii Chapter