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Titlebook: 6th Conference on Automated Deduction; New York, USA, June D. W. Loveland Conference proceedings 1982 Springer-Verlag Berlin Heidelberg 19

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Unbiasable Verifiable Random Functionsitives (layers 0 and 1) is described elsewhere[2]. The layer described here (layer 2) contains resolution- and equality-based inference rules, subsumption, and demodulation. It is designed to provide all of the tools required to create a theorem-prover with minimal effort. Although LMA is currently
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Succinct Homomorphic Secret Sharingge from simple bookkeeping and updating to the seeking of the generalization of two given formulas. Problems that one wishes to solve with the assistance of an automated theorem-proving program likewise often involve subsidiary tasks and the corresponding need for procedures (or their equivalent) to
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Hanlin Liu,Xiao Wang,Kang Yang,Yu Yue have found that Homogenization, described in [Bundy and Silver 81], can be extended to provide a fairly powerful method for solving these problems. The work described here has been implemented as an extension to PRESS, a computer program, written in PROLOG, [Clocksin and Mellish 81], for solving s
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Advances in Cryptology – EUROCRYPT 2024of two parts. Static structure combines information about the initial set of clauses and unifiers. Dynamic structure records information about the history of the deduction process (plan graph), about the unifications built in this process (graph of constraints), and about the conflicts encountered.
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https://doi.org/10.1007/978-3-031-58754-2d provides facilities to retrieve these facts. A retriever could range from a simple pattern matcher to a complete logical inference system. In practice, most fall in between these extremes, providing some forms of inference but not others. Unfortunately, most of these retrievers are not precisely d
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