As the number of the degrees of motion freedom increase in a robotic system, so grows the difficulty of control. We describe a model of a novel highly flexible robotic architecture composed of hundreds of motor elements, each associated with a unique degree of motion freedom. This new robotic architecture possesses a variably compliant structure that allows for the controlled distribution of loads and forces, and for the maintenance of different conformations. We then suggest two methods of intelligent control to manage the many motor elements. One method derives from neural networks, the other involves algorithms inspired by the biological immune system. Both methods are based on the system's perception of its own kinematics, and later self-prediction of the forces generated by coordinated subsets of motor elements that accomplish robot mobility and other work upon the environment.