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This paper describes the nature of mathematical discovery (including concept definition and exploration, example generation, and theorem conjecture and proof), and considers how such an intelligent process can be simulated by a machine. Although the material is drawn primarily from graph theory,...
We look at the representation within the framework of the approximate reasoning of relational type rules. A relational production rule consists of a rule in which one of the antecedent requirements involves the satisfaction of a relationship between two variables. An example of this type of rule...
We examine heuristic techniques for inducing production rules to cover artificially generated boolean expressions with irrelevant noise attributes. The results of different rule induction methods are compared, and it is shown that an iterative tree-based single-best-rule technique performs best...
In this paper we discuss reasoning about reasoning in a multiple agent scenario. We consider agents that are perfect reasoners, loyal, and that can take advantage of both the knowledge and ignorance of other agents. The knowledge representation formalism we use is (full) first order predicate...
Industrial and space applications present environments in which it is possible, and in fact desirable to solve robotic problems using a model-based approach. From a sensory standpoint, the reasons for employing knowledge about objects to be manipulated are twofold. First, such knowledge permits...
Knowledge base refinement is a learning process aimed at adjusting a knowledge base for the purpose of improving the breadth, accuracy, efficiency, and efficacy of the associated knowledge-based system(s). This annotated bibliography gives an overview of this emerging field.
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