Adaptation as a more powerful tool than decomposition and integration

摘要

Recently a new way of building control systems, known as behavior based robotics, has been proposed to overcome the difficulties of the traditional AI approach to robotics. Most of the work done in behavior-based robotics involves a decomposition process (in which the behavior required is broken down into simpler sub-components) and in an integration approach (in which the modules designed to produce the sub-behaviors are put together). In this paper we claim that the decomposition and integration process should be the result of an adaptation process and not of the decision of an experimenter. To support this hypothesis we show how in the case of a simple task in which a real autonomous robot is supposed to classify objects of different shapes, by letting the entire behavior emerge through an evolutionary technique, a more simple and robust solution can be obtained than by trying to design a set of modules and to integrate them.