MENTAL REPRESENTATIONS AND COGNITIVE BEHAVIOUR - A RECURRENT NEURAL NETWORK APPROACH

摘要

The ability of building up mental representations of external situations to uncouple the behaviour from direct environmental control can be considered to be a prerequisite for cognitive, adaptive behaviour. The network we present can be used for generation of action but also - due to its attractor characteristics - as a basis for mental representations. In this context, a new learning algorithm is proposed, which leads to a self-organised weight distribution yielding stable states and allows building up several cell assemblies existing simultaneously within a larger network.