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- W2219193831 abstract "The purpose of this paper is the dynamic locomotion control using a reinforcement learning of a microrobot with electromagnetic actuation (EMA) system based on Helmholtz, Maxwell and saddle type coils. The previous locomotion controls of the microrobot using EMA system have not considered the environmental disturbances such as an electromagnetic distortions and a blood flow. However, for the dynamic control of the microrobot in intravascular treatments, we should consider severe disturbances from the electromagnetic distortions and the pulsatile flow. Reinforcement learning is the machine learning in which a microrobot learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. The biggest problem of monolithic reinforcement learning is that its straight forward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest adaptive mediation-based modular Q-learning (AMMQL) as an improvement of the existing modular Q-learning. This paper introduces the concept of AMMQL and presents details of its application into dynamic locomotion of EMA System." @default.
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- W2219193831 date "2013-10-01" @default.
- W2219193831 modified "2023-09-26" @default.
- W2219193831 title "A Study on Adaptive Mediation-based Q-Learning for Dynamic Locomotion of Electromagnetic Actuated Microrobot System" @default.
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