Integration of context in process models used for neuro-control

We propose a new architectural model to deal with applications where the input space is very complex and high-dimensional. This solution is inspired from a classical connectionist approach and avoids saturation (A. Guez et al., 1988) due to the use of another connectionist structure, for memory storage. This model is very useful for control problems where input spaces are often complex and heterogeneous