The framework of multi-adjoint logic programming has shown to cover a number of approaches to reason under uncertainty, imprecise data or incomplete information. In previous works, we have presented a neural implementation of its fix-point semantics for a signature in which conjunctors are built as an ordinal sum of a finite family of basic conjunctors (Gödel and Łukasiewicz t-norms). Taking into account that a number of approaches to reasoning under uncertainty consider the set of subintervals of the unit interval as the underlying lattice of truth-values, in this paper we pursue an extension of the previous approach in order to accomodate calculation with truth-intervals. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Medina, J., Mérida-Casermeiro, E., & Ojeda-Aciego, M. (2005). Interval-valued neural multi-adjoint logic programs. In Lecture Notes in Computer Science (Vol. 3561, pp. 518–527). Springer Verlag. https://doi.org/10.1007/11499220_53
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