Abstract not found

Computing the least common subsumer (lcs) is an inference task that can be used to support the "bottom-up " construction of knowledge bases for KR systems based on description logics. Previous work on how to compute the lcs has concentrated on description logics that allow for universal value restrictions, but not for existential restrictions. The main new contribution of this paper is the treatment of description logics with existential restrictions. Our approach for computing the lcs is based on an appropriate representation of concept descriptions by certain trees, and a characterization of subsumption by homomorphisms between these trees. The lcs operation then corresponds to the product operation on trees.

representing the official policies, either expressed or implied, of the U.S. Government.

In this paper, we describe an investigation into the reuse and application of an existing ontology for the purpose of specifying and formally developing software for aircraft design. Our goals were to clearly identify the processes involved in the task, and assess the cost-effectiveness of reuse. Our conclusions are that (re)using an ontology is far from an automated process, and instead requires significant effort from the knowledge engineer. We describe and illustrate some intrinsic properties of the ontology translation problem and argue that fully automatic translators are unlikely to be forthcoming in the foreseeable future. Despite the effort involved, our subjective conclusions are that in this case knowledge reuse was cost-effective, and that it would have taken significantly longer to design the knowledge content of this ontology from scratch in our application. Our preliminary results are promising for achieving larger-scale knowledge reuse in the future.

This paper concentrates on query unnesting (also known as query decorrelation), an optimization that, even though improves performance considerably, is not treated properly (if at all) by most OODB systems. Our framework generalizes many unnesting techniques proposed recently in the literature and is capable of removing any form of query nesting using a very simple and efficient algorithm. The simplicity of our method is due to the use of the monoid comprehension calculus as an intermediate form for OODB queries. The monoid comprehension calculus treats operations over multiple collection types, aggregates, and quantifiers in a similar way, resulting in a uniform way of unnesting queries, regardless of their type of nesting.

Multi-stage programming languages provide a convenient notation for explicitly staging programs. Staging a definitional interpreter for a domain specific language is one way of deriving an implementation that is both readable and efficient. In an untyped setting, staging an interpreter "removes a complete layer of interpretive overhead", just like partial evaluation. In a typed setting however, Hindley-Milner type systems do not allow us to exploit typing information in the language being interpreted. In practice, this can have a slowdown cost factor of three or more times.

This paper provides foundations for a reasoning principle (coinduction) for establishing the equality of potentially infinite elements of self-referencing (or circular) data types. As it is well-known, such data types not only form the core of the denotational approach to the semantics of programming languages [SS71], but also arise explicitly as recursive data types in functional programming languages like Standard ML [MTH90] or Haskell [HPJW92]. In the latter context, the coinduction principle provides a powerful technique for establishing the equality of programs with values in recursive data types (see examples herein and in [Pit94]).

Denotational semantics [Sch86] is a powerful framework for describing programming languages; however, its descriptions lack modularity: conceptually independent language features influence each others' semantics. We address this problem by presenting a theory of modular denotational semantics. Following Mosses [Mos92], we divide a semantics into two parts, a computation ADT and a language ADT (abstract data type). The computation ADT represents the basic semantic structure of the language. The language ADT represents the actual language constructs, as described by a grammar. We define the language ADT using the computation ADT; in fact, language constructs are polymorphic over many different computation ADTs. Following Moggi [Mog89a], we build the computation ADT from composable parts, using monads and monad transformers. These techniques allow us to build many different computation ADTs, and, since our language constructs are polymorphic, many different language semantics. We autom...

This thesis introduces the language QML, a functional language for quantum computations on finite types. QML exhibits quantum data and control structures, and integrates reversible and irreversible quantum computations. The design of QML is guided by the categorical semantics: QML programs are in-terpreted by morphisms in the category FQC of finite quantum computations, which provides a constructive operational semantics of irreversible quantum computations, realisable as quantum circuits. The quantum circuit model is also given a formal categorical definition via the category FQC. QML integrates reversible and irreversible quantum computations in one language, using first order strict linear logic to make weakenings, which may lead to the collapse of the quantum wavefunction, explicit. Strict programs are free from measurement, and hence preserve superpositions and entanglement. A denotational semantics of QML programs is presented, which maps QML terms

Ontology concerns itself with the representation of the objects in the universe and the web of their various connections. The traditional task of ontologists has been to extract from this tangle a single ordered structure, in the form of a tree or lattice. This structure consists of the terms that represent the objects, and the relationships that represent connections between objects. Recent work in ontology goes so far as to consider several distinct, superimposed structures, which each represent a classification of the universe according to a particular criterion. Our purpose is to defer the task of globally classifying terms and relationships. Instead, we focus on composing them for use as we need them. We define contexts to be our unit of encapsulation for ontologies, and use a rule-based algebra to compose novel ontological structures within them. We separate context from concept, the unit of ontological abstraction. Also, we distinguish composition from subsumption, or containment, the relationships that commonly provide structure to ontologies. Adding a formal notation of encapsulation and composition to ontologies leads to more dynamic and maintainable structures, and, we believe, greater computational efficiency for knowledge bases.