As a test problem we first used the timetable problem and we developed a program that was applied to solve a real high school timetable. We also developed a program based on evolutionary algorithms to schedule the operations of a robotic system. The main goal of this research is to develop simulated robotic agents by the interplay of evolutionary and learning techniques. We start from basic very low-level building blocks, cells, which contain genetic information. A morphogenetic process let s cell duplicate and differentiate subject to environmental constraints.
Organisms so created can start, after the development phase, to reproduce.
In this way fittest, that is those individual who live longer, will have more offspring. During duplication new generated individuals undergo genetic changes like mutation and crossover. Learning capabilities are not designed into the system, but emerge as a consequence of their adaptive value.