Abstract
Being able to automatically analyze the search spaces of automated theorem provers is of the greatest importance. A method is proposed to do that. It is inspired by inductive tasks (e.g. discovering in mathematics and natural sciences). The key idea is to replace implicit genetic descriptions of the consequences in search spaces (i.e. the problem specification) by structural ones (describing the form of such consequences). The approach profits from the expressive power of term schematization languages and from the capabilities offered by existing powerful symbolic computation systems (Mathematica,...). A running software based on these ideas show evidence of the adequacy of the approach.
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Bensaid, H., Caferra, R., Peltier, N. (2007). Towards Systematic Analysis of Theorem Provers Search Spaces: First Steps. In: Leivant, D., de Queiroz, R. (eds) Logic, Language, Information and Computation. WoLLIC 2007. Lecture Notes in Computer Science, vol 4576. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73445-1_4
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DOI: https://doi.org/10.1007/978-3-540-73445-1_4
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