Evolving neural mechanisms for an iterated discrimination task: a robot based model
Tuci Elio, Ampatzis Christos, Dorigo Marco

Abstract:

This paper is about the design of an artificial neural network to control an autonomous robot that is required to iteratively solve a discrimination task based on time-dependent structures. The ``decision making'' aspect demands the robot ``to decide'', during a sequence of trials, whether or not the type of environment it encounters allows it to reach a light bulb located at the centre of a simulated world. Contrary to other similar studies, in this work the robot employs environmental structures to iteratively make its choice, without previous experience disrupting the functionality of its decision-making mechanisms.