A neural implementation of multi-adjoint logic programming
نویسندگان
چکیده
منابع مشابه
A neural implementation of multi-adjoint logic programming
We present a neural net based implementation of propositional [0, 1]-valued multiadjoint logic programming. The implementation needs some preprocessing of the initial program to transform it in a homogeneous program; then, transformation rules carry programs into neural networks, where truth-values of rules relate to output of neurons, truth-values of facts represent input, and network function...
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A synthesis of results of the recently introduced paradigm of multi-adjoint logic programming is presented. These results range from a proof theory together with some (quasi)completeness results to general termination results, and from the neural-like implementation of its fix-point semantics to the more general biresiduated multi-adjoint logic programming and its relationship with other approa...
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Multi-adjoint logic programs were recently proposed as a generalization of monotonic and residuated logic programs, in that simultaneous use of several implications in the rules and rather general connectives in the bodies are allowed. In this work, the need of biresiduated pairs is justified through the study of a very intuitive family of operators, which turn out to be not necessarily commuta...
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Considering different implication operators, such as Lukasiewicz, Gödel or product implication in the same logic program, naturally leads to the allowance of several adjoint pairs in the lattice of truthvalues. In this paper we apply this idea to introduce multi-adjoint logic programs as an extension of monotonic logic programs. The continuity of the immediate consequences operators is proved a...
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ژورنال
عنوان ژورنال: Journal of Applied Logic
سال: 2004
ISSN: 1570-8683
DOI: 10.1016/j.jal.2004.03.006