Levesque and Brachman argue that in order to provide timely and correct responses in the most critical applications, general purpose knowledge representation systems should restrict their languages by omitting constructs which require non-polynomial worst-case response times for sound and complete classification. They also separate terminological and assertional knowledge, and restrict classification to purely terminological information. We demonstrate that restricting the terminological language and classifier in these ways limits these "general-purpose" facilities so severely that they are no longer generally applicable. We argue that logical soundness, completeness, and worst-case complexity are inadequate measures for evaluating the utility of representation services, and that this evaluation should employ the broader notions of utility and rationality found in decision theory. We suggest that general purpose representation services should provide fully expressive languages, classi...

We consider the problem of integrating Reiter's default logic into terminological representation systems. It turns out that such an integration is less straightforward than we expected, considering the fact that the terminological language is a decidable sublanguage of first-order logic. Semantically, one has the unpleasant effect that the consequences of a terminological default theory may be rather unintuitive, and may even vary with the syntactic structure of equivalent concept expressions. This is due to the unsatisfactory treatment of open defaults via Skolemization in Reiter's semantics. On the algorithmic side, we show that this treatment may lead to an undecidable default consequence relation, even though our base language is decidable, and we have only finitely many (open) defaults. Because of these problems, we then consider a restricted semantics for open defaults in our terminological default theories: default rules are only applied to individuals that are explicitly presen...

We argue that rather than representing an agent's knowledge as a collection of formulas, and then doing theorem proving to see if a given formula follows from an agent's knowledge base, it may be more useful to represent this knowledge by a semantic model, and then do model checking to see if the given formula is true in that model. We discuss how to construct a model that represents an agent's knowledge in a number of different contexts, and then consider how to approach the model-checking problem.

classic is a recently developed knowledge representation (KR) system, based on a view of frames as structured descriptions, with several important inferable relationships, including description classification. While much about classic is novel and important in its own right, it is especially interesting to consider the system in light of its unusual (for Artificial Intelligence) intellectual history: it is the result of over a decade of research and evolution in representation systems that trace their origins back to work on kl-one, arguably one of the most long-lived and influential approaches to KR in the history of AI. We outline some of the novel contributions of classic, but pay special attention to its roots, illustrating the maturation of some of the original features of kl-one, and the decline and fall of others. A number of key ideas are analyzed---including the interpretation of frames as descriptions, the classification inference, and the role of a knowledge representation s...

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The formal analysis of semantic networks and frame systems led to the development of nonmonotonic inheritance networks and terminological logics. While nonmonotonic inheritance networks formalize the notion of default inheritance of typical properties, terminological logics formalize the notion of defining concepts and reasoning about definitions. Although it seems to be desirable to (re-)unify the two This work has been supported by the the Swedish National Board for Technical Development (STU) under grant # 9001669, by the Swedish Research Council for Engineering Sciences under grant # 900020, by the German Ministry for Research and Technology (BMFT) under research contract ITW 8901 8, and by the European Community as part of the ESPRIT Working Group DRUMS-II. approaches, such an attempt has not been made until now. In this paper, we will make a first step into this direction by specifying a nonmonotonic extension of a simple terminological logic. 1 Introduction The formal ana...

Default inheritance reasoning is a propositional approach to nonmonotonic reasoning designed to model reasoning with natural language generics. Inheritance reasoners model sets of natural language generics as directed acyclic graphs, and inference corresponds to the specification of paths through those networks. A proliferation of inheritance proof theories exist in the literature along with extensive debate about the most reasonable way to construct inferences, based on intuitions about interpretations of particular inheritance networks. There has not been an accepted semantics for inheritance which unifies the set of possible proof theories, which would help identify truly ill-motivated proof theories. This thesis attempts to clarify the inheritance literature in the three ways indicated in the title: psychological plausibility, proof theory and semantics. The thesis intends to displace debate about the best inferences to draw about a network from logicians ' introspections to empiri...

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Recently, there has been a debate over what the notion of inheritance means [1, 9, 13, 15, 16]. For example, Winkler [16] points to the dichotomy between the concept-oriented view (COV) and the program-oriented view (POV) of classes and inheritance. Wegner [15] has referred to COV as “logical” and POV as “physical. ” According to COV, squares form a subclass of rectangles. But this leads to some major problems in POV, where the set of operations applicable to a subclass is seen as a monotonic extension of its superclass. This is because applying operations such as “set-width ” to a square object would allow one to change the width of a square independently of its length. To remedy this situation, Winkler proposes an object-oriented view (OOV) of inheritance that replaces the term “class, ” “subclass ” and “superclass ” with “object type, ” “extension type ” and “base type, ” respectively. Winkler makes it seem to be a dichotomy of two different, overlapping but not identical, views of inheritance that can be resolved by renaming the concepts involved. But it turns out to be a more complex issue on deeper reflection. To realize the full complexity underlying the notion of inheritance, we must take a closer look at what Winkler has casually dubbed COV. Is inheritance from a conceptual point of view always (or often) unambiguous? Is a square always a rectangle? While one may be tempted to answer both these questions in the affirmative at first, a further reflection reveals that things are more subtle. For instance, if we were to just think of a class of all squares and a class of all rectangles, then obviously the former is a proper subclass of

A problem common to Computer Vision and Computer Graphics is identified. It is ',.he problem of representing, acquiring, and validating symbolic descriptions of visual properties. The intersection of Computer Vision and Computer Graphics provides a basis for diagrammatic conversations between users and systems. I call this problem domain Diagram Understanding because of its analogy with Natural Language Understanding. The recognition and generation of visual objects lom symbolic descriptions are two sides of the same coin. A paradigm for the discovery and validation of higher-level visual properties is introduced. The paradigm involves two aspects. One is the notion of alenotation: the map between symbolic descriptions and visual properties. The denotation map can be validated by focus on the conversation between users and a system. The second aspect inolves a method for discovering a natural and rich set of visual primitives. The notion of visual property is expanded, md the paradigm is further illustrated with a traditional business graphics example.