Add to ORKGAbstract. It is shown that, for some intersection and implication functions, an exact and efficient algorithm exists for the computation of inference results in multiconditional approximate reasoning on domains which are finite intervals of the real numbers, when membership functions are restricted to functions which are continuous and piecewise linear. An implementation of the algorithm is given in the functional programming language Miranda. 1
AbstractIn many areas of scientific inquiry, the phenomena under investigation are viewed as functio...
We propose a technique for dealing with the high complexity of reasoning under propositional default...
Many AI problems, when formulated, reduce to evaluating the probability that a prepositional express...
It is shown that, for some intersection and implication functions, an exact and efficient algorithm ...
It is shown that, for some intersection and implication functions, the complexity of the computation...
Methods are examined for finding an optimal least-squares approximation to a continuous function on ...
All rights reserved. An algorithm is described for approximating a function F(x) on a finite interva...
We present an efficient algorithm for approximate reasoning with multiple antecedents. This algorith...
The class of continuous piecewise linear (PL) functions represents a useful family of approximants b...
AbstractThis paper investigates the relationship between approximation error and complexity. A varie...
The class of continuous piecewise linear (PL) functions represents a useful family of approximants b...
AbstractMany AI problems, when formalized, reduce to evaluating the probability that a propositional...
We consider a representation for temporal relations between intervals introduced by James Allen, and...
This paper investigates the relationship between approximation error and complexity. A variety of co...
AbstractThis is a follow-up paper of “Liberating the dimension for function approximation”, where we...
AbstractIn many areas of scientific inquiry, the phenomena under investigation are viewed as functio...
We propose a technique for dealing with the high complexity of reasoning under propositional default...
Many AI problems, when formulated, reduce to evaluating the probability that a prepositional express...
It is shown that, for some intersection and implication functions, an exact and efficient algorithm ...
It is shown that, for some intersection and implication functions, the complexity of the computation...
Methods are examined for finding an optimal least-squares approximation to a continuous function on ...
All rights reserved. An algorithm is described for approximating a function F(x) on a finite interva...
We present an efficient algorithm for approximate reasoning with multiple antecedents. This algorith...
The class of continuous piecewise linear (PL) functions represents a useful family of approximants b...
AbstractThis paper investigates the relationship between approximation error and complexity. A varie...
The class of continuous piecewise linear (PL) functions represents a useful family of approximants b...
AbstractMany AI problems, when formalized, reduce to evaluating the probability that a propositional...
We consider a representation for temporal relations between intervals introduced by James Allen, and...
This paper investigates the relationship between approximation error and complexity. A variety of co...
AbstractThis is a follow-up paper of “Liberating the dimension for function approximation”, where we...
AbstractIn many areas of scientific inquiry, the phenomena under investigation are viewed as functio...
We propose a technique for dealing with the high complexity of reasoning under propositional default...
Many AI problems, when formulated, reduce to evaluating the probability that a prepositional express...