The Evolution of Motivated and Modulated Robot Selection

In this paper we focus on the development of a selection model that allows a robot to select pre-evolved behaviour in a motivated environment. A collection task is set in an arena where the Khepera robot has to collect cylinders, which simulate food. Therefore, two basic motivations, labelled as 'obesity' and 'anorexia', both affect the selection of the behavioural repertoire. Additionally, in this model is possible to modulate the model to be either more or less selective depending on the tonic value of the simulated 'mesolimbic/cortical tone'. Next, we use evolution for optimizing the motivated selection network employed for behavioural switching. Finally, we describe the results of varying, by hand and evolution, the levels of reward by the mesolimbic-cortical tone.