01144nas a2200133 4500008004100000245011300041210006900154260002100223300001200244520067200256100002200928700002000950856004000970 2003 eng d00aContinuity of Semantic Operators in Logic Programming and their Approximation by Artificial Neural Networks.0 aContinuity of Semantic Operators in Logic Programming and their aHamburg, Germany a105-1193 aOne approach to integrating First-order logic programming and neural network systems employs the approximation of semantic operators by feedforward networks. For this purpose, it is necessary to view these semantic operators as continuous functions on the reals. This can be accomplished by endowing the space of all interpretations of a logic program with topologies obtained from suitable embeddings. We will present such topologies which arise naturally out of the theory of logic programming, discuss continuity issues of several wellknown semantic operators, and derive some results concerning the approximation of these operators by feedforward neural networks.1 aSeda, Anthony, K.1 aHitzler, Pascal uhttp://knoesis.wright.edu/node/1204