An approach to abductive inference developed in the TACITUS project has resulted in a dramatic simplification of how the problem of interpreting texts is conceptualized. Its use in solving the local pragmatics problems of reference, compound nominals, syntactic ambiguity, and metonymy is described and illustrated. It also suggests an elegant and thorough integration of syntax, semantics, and pragmatics. 1

In the following report, we describe a new shell for building abductive problem solving agents. This shell, called Peirce-IGTT 1 , can be used in conjunction with other problem solving tools constructed at the Laboratory for Artificial Intelligence Research at The Ohio State University in order to build large knowledgebased systems. Peirce itself is a tool for building agents to solve the abductive tasks of hypothesis assembly and critique. This report will discuss the Peirce tool and its algorithm, some brief history of the construction of the tool and a sample case that was constructed from it. Abductive Problem Solving Abduction is inference to the best explanation[9]. It is a form of problem solving where hypotheses are formed and selected to explain a set of data or findings. This form of inference can be used in solving diagnostic and related sort of problems[5, 6, 12, 14, 19]. In attempting to solve an abductive problem, there generally needs to be a means to generate hypothe...

Abduction is inference to the best explanation. In the TACITUS project at SRI we have developed an approach to abductive inference, called "weighted abduction", that has resulted in a significant simplification of how the problem of interpreting texts is conceptualized. The interpretation of a text is the minimal explanation of why the text would be true. More precisely, to interpret a text, one must prove the logical form of the text from what is already mutually known, allowing for coercions, merging redundancies where possible, and making assumptions where necessary. It is shown how such "local pragmatics " problems as reference resolution, the interpretation of compound nominals, the resolution of syntactic ambiguity and metonymy, and schema recognition can be solved in this manner. Moreover, this approach of "interpretation as abduction " can be combined with the older view of "parsing as deduction " to produce an elegant and thorough integration of syntax, semantics, and pragmatics, one that spans the range of linguistic phenomena from phonology to discourse structure. Finally, we discuss means for making the abduction process efficient, possibilities for extending the approach to other pragmatics phenomena, and the semantics of the weights and costs in the abduction scheme. 1

have developed an approach to abductive inference, called "weighted abduction", that has resulted in a significant simplification of how the problem of interpreting texts is conceptualized. The interpretation of a text is the minimal explanation of why the text would be true. More precisely, to interpret a text, one must prove the logical form of the text from what is already mutually known, allowing for coercions, merging redundancies where possible, and making assumptions where necessary. It is shown how such "local pragmatics " problems as reference resolution, the interpretation of compound nominals, the resolution of syntactic ambiguity and metonymy, and schema recognition can be solved in this manner. Moreover, this approach of "interpretation as abduction " can be combined with the older view of "parsing as deduction " to produce an elegant and thorough integration of syntax, semantics, and pragmatics, one that spans the range of linguistic phenomena from phonology to discourse structure. Finally, we discuss means for making the abduction process efficient, possibilities for extending the approach to other pragmatics phenomena, and the semantics of the weights and costs in the abduction scheme. 1.

This report describes the project. We first describe the problem, followed by a description of the solution by way of a three-level abduction problem solver. This is followed by discussion of experiments run on this problem solver and the results of these experiments. Going into the project, we hoped to show that a multi-layered abduction machine was feasible and more able to solve problems than non-abductive and single-layered problem solvers. Articulatory Recognition

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DEGREE: Doctor of Philosophy