  In mobile robotics, a solid test for adaptation is the ability of a control
system to function not only in a diverse number of physical environments, but
also on a number of different robotic platforms. This paper demonstrates that a
set of behaviours evolved in simulation on a miniature robot (epuck) can be
transferred to a much larger-scale platform (Pioneer), both in simulation and
in the real world. The chosen architecture uses artificial evolution of epuck
behaviours to obtain a genetic sequence, which is then employed to seed an
idiotypic, artificial immune system (AIS) on the Pioneers. Despite numerous
hardware and software differences between the platforms, navigation and
target-finding experiments show that the evolved behaviours transfer very well
to the larger robot when the idiotypic AIS technique is used. In contrast,
transferability is poor when reinforcement learning alone is used, which
validates the adaptability of the chosen architecture.
