To validate this hypothesis, we simulated the reinforcement of the synergistic actions of the two control policies during the reinforcement learning of feedback motion control. The individual control policy (ICP) assists the GCP in precisely controlling motion by controlling individual muscle units. This policy is used to effectively resist external dynamic circumstances, such as disturbances. One of the policies is the group control policy (GCP), which is used to control muscle group units classified based on functional similarities in joint control. Our assumption is based on biological evidence regarding the control of multiple muscles via the corticospinal tract. We propose that two main muscle control policies synergistically control muscle units to maintain the desired motion against external dynamic conditions. To address this issue, we considered a new muscle synergy concept used to optimize the synergy between muscle units against external dynamic conditions, including novel conditions. As a result, they have been unable to analyze how muscle synergy contributes to motion control robustness in a biological system. However, previous related studies have usually simplified the control of multiple muscles using two opposing muscles, which are minimum actuators to simulate linear feedback control. To accomplish this, the brain needs to optimize the synergistic control between muscles against external dynamic factors. Humans are able to robustly maintain desired motion and posture under dynamically changing circumstances, including novel conditions.

Muscle synergy model