— This paper applies a recently developed neural network called plausible neural network (PNN) to function approximation. Instead of using error correction, PNN estimates the mut...
Wavelet neural networks (WNN) have recently attracted great interest, because of their advantages over radial basis function networks (RBFN) as they are universal approximators bu...
The main difficulty in the formalization of a static analysis framework for CC programs is probably related to the correct approximation of the entailment relation between constrai...
Large scale ontology applications require efficient and robust description logic (DL) reasoning services. Expressive DLs usually have very high worst case complexity while tractab...
Universal induction solves in principle the problem of choosing a prior to achieve optimal inductive inference. The AIXI theory, which combines control theory and universal induct...