Dynamical neural network algorithm for autonomous learning and navigation control

We present a model of spatial navigation based on the KIII dynamical model of perception developed by Walter Freeman in the 70´s. We use a KIII model of the hippocampus that learns global orientation based on pre-defined landmarks and a KIII model of the sensory cortex that provides local sensory information about obstacles. We test the model using a task that requires the exploration of a previously unknown environment and the navigation towards a goal location. Computer simulations show that the simulated agent learns the position of the goal. The model provides a novel description of how navigation and way finding in the style of the brain.