A neurocomputational model implemented on humanoid robot for learning action selection

Abstract

Computational modeling of neural circuits enhances our comprehension of brain functions. In addition to the simulation of the models which helps to anticipate cognitive processes, embodiment of these models is essential. Such embodiment would provide the setting to explain neural functioning ongoing in real environments under oncoming sensory information besides giving opportunity of implementation of intelligent systems. Even studies pursued in neuroscience seem far from achieving all these aims in intelligent systems, the pre-results using cognitive models are faster than animal experiments in leading further the understanding of cognitive processes and designing related experiments.