First published 2 July 2012
With a little help from selection pressures: evolution of memory in robot controllers
Charles Ollion, Tony Pinville, Stéphane Doncieux
Evolutionary robotics (ER) have successfully built robot controllers presenting a reactive behavior. However, the evolution of cognitive controllers is still a challenge. We hypothesize here that a fitness function which rewards the fulfillment of a task requiring cognitive abilities does not necessarily reward the stepping stones that lead to cognitive controllers. In other words, our hypothesis is that evolving cognitive abilities is a deceptive problem, and that the selective pressures driving the evolutionary search are of critical importance. This paper presents some experiments to confirm this hypothesis and addresses this selective pressure problem by introducing a new helper-objective that rewards controllers with a memory. This is potentially useful for the design of controllers in which an internal representation of some data is required to solve a task. It does not assume how the memory is stored in the controller, therefore reducing the bias towards a particular solution. The new objective is tested in a multi-objective scheme on a T-maze ER task &mdasdh; a task involving both navigation and working memory. The efficiency of the helperobjective is studied, as well as its effects on the overall performance and generalization ability of the controller.