همکاری تالامیم بین مخچه و گانگلیس پایه با یک روش برنامه ریزی پویای اکتشافی وابسته به عمل مبتنی بر تروپیسم

In order to explore the possible cooperation mechanism between the cerebellum and basal ganglia in the central nervous system and to establish a more intelligent learning mechanism for robots, a new tropism-based ADHDP (action-dependent heuristic dynamic programming) learning mechanism involving the cortico-basal ganglia and cerebellar circuitry and the thalamic function is proposed. The cerebellum specializes in the actor part, while the basal ganglia are related to critic prediction. The thalamic function is considered as the tropism mechanism. Tropism value denoting the biological propensity is introduced to illustrate the degree of closing to the target. Although several motor control models have been proposed to explain the control and learning mechanism in the cerebellum and basal ganglia separately, it seems that the cooperation mechanism between them has not received much attention. In our proposed learning mechanism, the thalamic function and the cooperation between the cerebellum and basal ganglia are considered, and with a neurophysiological view, a striato-striatal lateral weight in the basal ganglia was added in the critic network. We present the detailed design architecture and explain how effective learning and optimization can be achieved with this novel tropism-based ADHDP architecture. Furthermore, we test its performance on the balance learning task of a two-wheeled self-balancing robot (TWSBR), which simulates the typical motor control and learning of the human body. In order to illustrate the effect of the thalamic function, some comparison researches about the balance learning problem have been done.