Granularity-Adaptive Proof Presentation

Details Granularity-Adaptive Proof Presentation Granularity-Adaptive Proof Presentation

2009-03-02

arxiv.org/abs/0903.0314v4

Computer Science

Artificial Intelligence

Extended Version. This SEKI Working-Paper refines and extends the following publication: Granularity-Adaptive Proof Presentati

Scientific paper

When mathematicians present proofs they usually adapt their explanations to their didactic goals and to the (assumed) knowledge of their addressees. Modern automated theorem provers, in contrast, present proofs usually at a fixed level of detail (also called granularity). Often these presentations are neither intended nor suitable for human use. A challenge therefore is to develop user- and goal-adaptive proof presentation techniques that obey common mathematical practice. We present a flexible and adaptive approach to proof presentation that exploits machine learning techniques to extract a model of the specific granularity of proof examples and employs this model for the automated generation of further proofs at an adapted level of granularity.

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