The Effect of Sensory Information on Reinforcement Learning by a Robot Arm

In this paper we present an application of ALECSYS, a distributed learning classifier system, to the control of a robot arm. ALECSYS is initialised with a set of randomly generated rules and is trained to control a robot arm whose task is to reach a non moving light source. At this point of our research our results are relative to the simulation of a real robot arm (IBM 7547 with a SCARA geometry), which will be the target of the final implementation of our learning system.