Extended model of conditioned learning within latent inhibition

Due to the various and dynamic nature of stimuli, decisions of intelligent agents must rely on the coordination of complex cognitive systems. This paper precisely focusses on a general learning architecture for autonomous agents. It is based on a neural network model that enables the specific behaviours of classical conditioning and a biologically inspired attentional phenomenon called latent inhibition. We propose a neural network implementation of an extended model of classical conditioning and present some results.

• Type: Conference
• Year: 2006
• Where: ESANN
• Authors: Nicolas Gomond, Jean Marc Salotti
• Keywords: Classical Conditioning, ESANN 2006, ESANN 2007, Neural Network, Neural Network Model