This thesis studies planning problems whose solution plans are program-like structures that contain branches and loops. Such problems are a generalization of classical and conditional planning, and usually involve infinitely many cases to be handled by a single plan. This form of planning is useful in a number of applications, but meanwhile challenging to analyze and solve. As a result, it is drawing increasing interest in the AI community. In this thesis, I will give a formal definition of planning with loops in the situation calculus framework, and propose a corresponding plan representation in the form of finite-state automata. It turns out that this definition is more general than a previous formalization that uses restricted programming structures for plans. For the verification of plans with loops, we study a property of planning problems called finite verifiability. Such problems have the property that for any candidate plan, only a finite number of cases need to be checked in order to conclude whether the plan is correct for all the infinitely many cases. I will identify several forms of finitely-verifiable classes of planning problems, including the so-called one-dimensional problems where an unknown and unbounded number of objects need independent processing. I will also show that this property is not universal, in that finite verifiability of less restricted problems would mean a solution to the Halting problem or an unresolved mathematical conjecture. For the generation of plans with loops, I will present a novel nondeterministic algorithm which essentially searches in the space of the AND/OR execution trees of an incremental partial plan on a finite set of example instances of the planning problem. Two different implementations of the algorithm are explored for search efficiency, namely, heuristic search and randomized search with restarts. In both cases, I will show that the resulting planner generates compact plans for a dozen benchmark problems, some of which are not solved by other existing approaches, to the best of our knowledge. Finally, I will present generalizations and applications of the framework proposed in this thesis that enables the analysis and solution of related planning problems recently proposed in the literature, namely, controller synthesis, service composition and planning programs. Notably, the latter two require possiblynon-terminating execution in a dynamic environment to provide services to coming requests. I will show a generic definition and planner whose instantiation accommodates and solves all the three example applications. Interestingly, the instantiations are competitive with, and sometimes even outperform, the original tailored approaches proposed in the literature.

This thesis studies planning problems whose solution plans are program-like structures that contain branches and loops. Such problems are a generalization of classical and conditional planning, and usually involve infinitely many cases to be handled by a single plan. This form of planning is useful in a number of applications, but meanwhile challenging to analyze and solve. As a result, it is drawing increasing interest in the AI community. In this thesis, I will give a formal definition of planning with loops in the situation calculus framework, and propose a corresponding plan representation in the form of finite-state automata. It turns out that this definition is more general than a previous formalization that uses restricted programming structures for plans. For the verification of plans with loops, we study a property of planning problems called finite verifiability. Such problems have the property that for any candidate plan, only a finite number of cases need to be checked in order to conclude whether the plan is correct for all the infinitely many cases. I will identify several forms of finitely-verifiable classes of planning problems, including the so-called one-dimensional problems where an unknown and unbounded number of objects need independent processing. I will also show that this property is not universal, in that finite verifiability of less restricted problems would mean a solution to the Halting problem or an unresolved mathematical conjecture. For the generation of plans with loops, I will present a novel nondeterministic algorithm which essentially searches in the space of the AND/OR execution trees of an incremental partial plan on a finite set of example instances of the planning problem. Two different implementations of the algorithm are explored for search efficiency, namely, heuristic search and randomized search with restarts. In both cases, I will show that the resulting planner generates compact plans for a dozen benchmark problems, some of which are not solved by other existing approaches, to the best of our knowledge. Finally, I will present generalizations and applications of the framework proposed in this thesis that enables the analysis and solution of related planning problems recently proposed in the literature, namely, controller synthesis, service composition and planning programs. Notably, the latter two require possiblynon-terminating execution in a dynamic environment to provide services to coming requests. I will show a generic definition and planner whose instantiation accommodates and solves all the three example applications. Interestingly, the instantiations are competitive with, and sometimes even outperform, the original tailored approaches proposed in the literature.

Thesis (Ph.D )--Tufts University, 2000. / Adviser: James G. Schmolze. Submitted to the Dept. of Computer Science. Includes bibliographical references (leaves 148-156). Access restricted to members of the Tufts University community. Also available via the World Wide Web;

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1991. / Vita. Abstract. Includes bibliographical references (leaves 93-94). Also available via the Internet.

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This research is concerned with designing representations for analytical reasoning problems (of the sort found on the GRE and LSAT). These problems test the ability to draw logical conclusions. A computer program was developed that takes as input a straightforward predicate calculus translation of a problem, requests additional information if necessary, decides what to represent and how, designs representations capturing the constraints of the problem, and creates and executes a LISP program that uses those representations to produce a solution. Even though these problems are typically difficult for theorem provers to solve, the LISP program that uses the designed representations is very efficient.

In this paper we study three OPAC interfaces of K.U.Leuven University Library. All three interfaces have been on-line between 2002 and 2005. The characteristics of these OPACs (search fields, labeling of the fields, search facilities, searching vs. browsing, basic vs. advanced search) are systematically examined. Special attention is given to subject search and display, and more specifically to Universal Decimal Classification (UDC) and Medical Subject Headings (MeSH). This comparison is particularly interesting because the indexing and classification tools (UDC, Library of Congress Subject Headings, MeSH) remain the same in all three OPACs. However, the way these tools are presented for subject retrieval in the respective OPACs undergoes an interesting evolution. It is demonstrated that subject search and display in library catalogs can be largely improved by investing in optimal use of existing tools. We also stress the importance of user-oriented OPAC design.

K.U.Leuven University Library (Belgium) developed an experimental interface for subject search by UDC in the OPAC. The interface combines the search facilities of a classification with those of a word system, since it enables the end user to search by subject terms and to see these terms in the hierarchy of broader, parallel and more specific terms. This project should be seen as an important indication of the libraryâ s growing concern to present its information sources in a content-structured and user-friendly way. At the same time, it has to be situated in a new policy for knowledge organization, which aims to find a balance between the local and overall needs of a library network. Finally, this project comes at a moment when K.U.Leuven University Library is in full conversion to Aleph 500 software.