Neuro-ACT Cognitive Architecture Applications in Modeling Driver’s Steering Behavior in Turns

Cognitive Architectures (CAs) are the core of artificial cognitive systems. A CA is supposed to specify the human brain at a level of abstraction suitable for explaining how it achieves the functions of the mind. Over the years a number of distinct CAs have been proposed by different authors and their limitations and potentials were investigated. These CAs are usually classified as symbolic and sub-symbolic architectures. In this work, a novel hybrid architecture is proposed that encompasses a symbolic part (i.e. ACT-R) to explain the controlled aspects of behavior and a sub-symbolic part (i.e. Artificial Neural Networks) to describe automated skills. In order to demonstrate the capabilities of the proposed model, an experiment was conducted in which, a rather complex real life task was carried out by the model and its result were compared with those of human participants. Simulation results have shown promising capabilities of the new architecture in modeling complex human behavior.