Understanding Natural Language
Understanding Natural Language
IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 1
Implementing a model of human plausible reasoning
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
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The paper outlines a computational theory of human plausible reasoning constructed from analysis of people's answers to everyday questions. Like logic, the theory is expressed in a content-independent formalism. Unlike logic, the theory specifies how different information in memory affects the certainty of the conclusions drawn. The theory consists of a dimensionalized space of different inference types and their certainty conditions, including a variety of meta-inference types where the inference depends on the person's knowledge about his own knowledge. The protocols from people's answers to questions are analyzed in terms of the different inference types. The paper also discusses how memory is structured in multiple ways to spport the different inference types, and how the information found in memory determines which inference types are triggered.