Biological information processing systems can be said to be one of the
ultimate decentralized systems and have been expected to provide vari
ous fruitful ideas to engineering fields, especially robotics. Among t
hese systems, brain-nervous and genetic systems have already been wide
ly used in modeling as neural networks and genetic algorithms, respect
ively. On the other hand, the immune system also plays an important ro
le in coping with a dynamically changing environment by constructing s
elf-non-self recognition networks among different species of antibodie
s. This system has many interesting features such as learning, self-or
ganizing abilities, etc., viewed from the engineering standpoint. Ther
efore, it can be expected to provide novel approaches to the PDP parad
igm. However, the immune system has not yet been applied to engineerin
g fields. In this paper, we propose a new hypothesis concerning the st
ructure of the immune system, called the mutual-coupled immune network
s hypothesis, based on recent studies on immunology. We apply this ide
a to gait acquisition of a hexapod walking robot as a practical exampl
e. Finally, the feasibility of our proposed method is confirmed by sim
ulations.