211 research outputs found

    Asymptotics for the number of n-quasigroups of order 4

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    The asymptotic form of the number of n-quasigroups of order 4 is 3n+122n+1(1+o(1))3^{n+1} 2^{2^n +1} (1+o(1)). Keywords: n-quasigroups, MDS codes, decomposability, reducibility.Comment: 15 p., 3 fi

    On the number of n-ary quasigroups of finite order

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    Let Q(n,k)Q(n,k) be the number of nn-ary quasigroups of order kk. We derive a recurrent formula for Q(n,4). We prove that for all n2n\geq 2 and k5k\geq 5 the following inequalities hold: (k3/2)n/2(k12)n/2<log2Q(n,k)ck(k2)n({k-3}/2)^{n/2}(\frac{k-1}2)^{n/2} < log_2 Q(n,k) \leq {c_k(k-2)^{n}} , where ckc_k does not depend on nn. So, the upper asymptotic bound for Q(n,k)Q(n,k) is improved for any k5k\geq 5 and the lower bound is improved for odd k7k\geq 7. Keywords: n-ary quasigroup, latin cube, loop, asymptotic estimate, component, latin trade.Comment: english 9pp, russian 9pp. v.2: corrected: initial data for recursion; added: Appendix with progra

    The use of data-mining for the automatic formation of tactics

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    This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques
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