— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
We identify two fundamental points of utilizing CBR for an adaptive agent that tries to learn on the basis of trial and error without a model of its environment. The first link co...
— Inspired by Hebb’s cell assembly theory about how the brain worked, we have developed a function localization neural network (FLNN). The main part of a FLNN is structurally t...
By strictly separating reconfigurable logic from their host processor, current custom computing systems suffer from a significant communication bottleneck. In this paper we descri...
Scott Hauck, Thomas W. Fry, Matthew M. Hosler, Jef...
The shaky ladder hyperplane-defined functions (sl-hdf's) are a test suite utilized for exploring the behavior of the genetic algorithm (GA) in dynamic environments. We present...