An artificial multiped is constructed (either in simulation or embodied)
in such a way that its natural body dynamics allow the lower part of each
leg to swing naturally under the influence of gravity. The upper part of
each leg is actively actuated in the sagittal plane. The necessary input
to drive the above-mentioned actuators is derived from a neural network
controller. The latter is arranged as two bi-directionally coupled chains
of neural oscillators, the number of which equals twice that of the legs
to be actuated. Parameter optimisation of the controllers is achieved by
evolutionary computation in the form of a genetic algorithm.