A　computational　model　in　the　framework　of　reinforcement　learning,　called　Cooperative　Motor　Learning　(CML)　model,　is　proposed　to　realize　cerebellar　control　of　balance　and　locomotion.　In　the　CML　model,　cerebellum　is　a　parallel　pathway　that　the　vermis　and　the　flocculonodular　lobe　play　a　role　of　reflex　actions　executor,　and　that　the　intermediate　zone　of　the　cerebellum　participates　in　initiating　voluntary　actions.　During　the　training　phase,　the　cerebral　cortex　provides　the　predictive　error　through　climbing　fiber　to　modulate　the　concurrently　activated　synapses　between　parallel　fibers　and　purkinje　cells.　Meanwhile,　the　intermediate　zone　of　the　cerebellum　computes　the　temporal　difference　(TD)　error　as　a　training　signal　for　the　cerebral　cortex.　In　the　simulation　experiment　for　the　balance　of　double　inverted　pendulum　on　a　cart,　a　well-trained　CML　model　can　smoothly　push　the　pendulum　into　the　equilibrium　position.　©　Springer-Verlag　Berlin　Heidelberg　2006.