Abstract
Our approach to improve the search of a theorem prover employs empirical knowledge gained from former proofs. A connectionist network is used to learn heuristics which order the choices at nondeterministic branch-points. This is done by estimating their relative chance for leading to a shortest proof. Using the method it was possible to reduce the search effort required by a high speed theorem prover. Several experiments are presented showing the attained improvements.
This paper was supported by the Nixdorf Computer AG within ESPRIT project 415 F.
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Suttner, C., Ertel, W. (1990). Automatic acquisition of search guiding heuristics. In: Stickel, M.E. (eds) 10th International Conference on Automated Deduction. CADE 1990. Lecture Notes in Computer Science, vol 449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-52885-7_108
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DOI: https://doi.org/10.1007/3-540-52885-7_108
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