John R. Josephson

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The problem of abduction can be characterized as nding the best explanation of a set of data. In this paper we focus on one type of abduction in which the best explanation is the most plausible combination of hypotheses that explains all the data. We then present several computational complexity results demonstrating that this type of abduction is(More)
THEORIES IN AI FALL INTO TWO broad categories: mechanism theories and content theories. Ontologies are content theories about the sorts of objects, properties of objects, and relations between objects that are possible in a specified domain of knowledge. They provide potential terms for describing our knowledge about the domain. In this article, we survey(More)
We explore the meanings of the terms ‘structure’, ‘behaviour’, and, especially, ‘function’ in engineering practice. Computers provide great assistance in calculation tasks in engineering practice, but they also have great potential for helping with reasoning tasks. However, realising this vision requires precision in representing engineering knowledge, in(More)
Much of the work on ontologies in AI has focused on describing some aspect of reality: objects, relations, states of affairs, events, and processes in the world. A goal is to make knowledge sharable, by encoding domain knowledge using a standard vocabulary based on the ontology. A parallel attempt at identifying the ontology of problem-solving knowledge has(More)
Only for you today! Discover your favourite abduction reason and science processes of discovery and explanation book right here by downloading and getting the soft file of the book. This is not your time to traditionally go to the book stores to buy a book. Here, varieties of book collections are available to download. One of them is this abduction reason(More)
In the following report, we describe a new shell for building abductive problem solving agents. This shell, called Peirce-IGTT1, can be used in conjunction with other problem solving tools constructed at the Laboratory for Arti cial Intelligence Research at The Ohio State University in order to build large knowledgebased systems. Peirce itself is a tool for(More)
T h e p rob lem of f inding a best exp lana t ion of a set of da ta has been a top ic of m u c h interest in A r t i f i c i a l I n t e l l i gence. In th is paper we present an approach to th is p r o b l e m by hypothesis assembly. We present th is approach f o rma l l y so tha t we can examine the t ime comp lex i t y and correctness of the a lgo r i t(More)