We deal with directed hypergraphs as a tool to model and solve some classes of problems arising in Operations Research and in Computer Science. Concepts such as connectivity, paths and cuts are defined. An extension of the main duality results to a special class of hypergraphs is presented. Algorithms to perform visits of hypergraphs and to find optimal paths are studied in detail. Some applications arising in propositional logic, And-Or graphs, relational data bases and transportation analysis are presented. January 1990 Revised, October 1992 ( * ) This research has been supported in part by the "Comitato Nazionale Scienza e Tecnologia dell'Informazione", National Research Council of Italy, under Grant n.89.00208.12, and in part by research grants from the National Research Council of Canada. 1 Dipartimento di Informatica, Università di Pisa, Italy 2 Département d'Informatique et de Recherche Opérationnelle, Université de Montréal, Canada 2 INTRODUCTION Hypergraphs, a generaliz...

Induction of recursive theories in the normal ILP setting is a difficult learning task whose complexity is equivalent to multiple predicate learning. In this paper we propose computational solutions to some relevant issues raised by the multiple predicate learning problem. A separate-andparallel -conquer search strategy is adopted to interleave the learning of clauses supplying predicates with mutually recursive definitions. A novel generality order to be imposed on the search space of clauses is investigated, in order to cope with recursion in a more suitable way. The consistency recovery is performed by reformulating the current theory and by applying a layering technique, based on the collapsed dependency graph. The proposed approach has been implemented in the ILP system ATRE and tested on some laboratory-sized and real-world data sets. Experimental results demonstrate that ATRE is able to learn correct theories autonomously and to discover concept dependencies. Finally, related works and their main differences with our approach are discussed.

We describe a formalism based on the proof theory of linear logic, whose aim is to specify concurrent computations and whose language restriction (as compared to other linear logic languages) provides a simpler operational model that can lead to a more practical language core. The fragment is proved to be an abstract logic programming language, that is any sequent can be derived by uniform proofs. The resulting class of computations can be viewed in terms of multiset rewriting and is reminiscent of the computations arising in the Chemical Abstract Machine and in the Gamma model. The fragment makes it possible to give a logic foundation to existing extensions of Horn clause logic, such as Generalized Clauses, whose declarative semantics is based on an ad hoc construction. Programs and goals can declaratively be characterized by a suitable instance of the phase semantics of linear logic. A canonical phase model is associated to every program. Such a model gives a full characterization of...

We address a generalization of graphs, the directed hypergraphs, and show that they are a powerful tool in modelling and solving several relevant problems in many application areas. Such application areas include Linear Production Problems, Flexible Manufacturing Systems, Propositional Logic, Relational Databases, and Public Transportation Systems.

: Based on a theoretical framework of problem solving and knowledge acquisition, criteria for intelligent knowledge communication systems and help design are described. The ABSYNT Problem Solving Monitor for the acquisition of basic functional programming concepts in a visual language is designed according to these criteria. It incorporates hypotheses testing of solution proposals, and a learner model is designed to supply user-adapted help. New is a third feature, which is presented in this paper: Planning programs with goal nodes. The learner can develop solution plans by postponing their implementation, and it is possible to test hypotheses with partial plans and with "mixed trees", existing of operator and goal nodes. The planning component of ABSYNT rests on a sound transformation approach (Bauer et al., 1987) that enables the derivation of functional programs from specifications. We hope to make derivational programming accessible even to beginners in very early stage...

Document image understanding denotes the recognition of semantically relevant components in the layout extracted from a document image. This recognition process is based on some visual models, whose manual specification can be a highly demanding task. In order to automatically acquire these models, we propose the application of machine learning techniques. In this paper, problems raised by possible dependencies between concepts to be learned are illustrated and solved with a computational strategy based on the separate-and-parallel-conquer search. The approach is tested on a set of real multi-page documents processed by the system WISDOM++. New results confirm the validity of the proposed strategy and show some limits of the learning system used in this work.

Summary. Document image understanding refers to logical and semantic analysis of document images in order to extract information understandable to humans and codify it into machine-readable form. Most of the studies on document image understanding have targeted the specific problem of associating layout components with logical labels, while less attention has been paid to the problem of extracting relationships between logical components, such as cross-references. In this chapter, we investigate the problem of detecting the reading order relationship between components of a logical structure. The domain specific knowledge required for this task is automatically acquired from a set of training examples by applying a machine learning method. The input of the learning method is the description of “chains” of layout components defined by the user. The output is a logical theory which defines two predicates, first to read/1 and succ in reading/2, useful for consistently reconstructing all chains in the training set. Only spatial information on the page layout is exploited for both single and multiple chain reconstruction. The proposed approach has been evaluated on a set of document images processed by the system WISDOM++. 1