Evolving Neural Mechanisms for an Iterated Discrimination Task: A Robot Based Model

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.

• Type: Conference
• Year: 2005
• Where: ECAL
• Authors: Elio Tuci, Christos Ampatzis, Marco Dorigo
• Keywords: Artificial Neural Network, Autonomous Robot, ECAL 2005, Time-dependent Structures