Contribution of explicit processes to reinforcement-based motor learning

Implicit and Explicit Processes in Motor Learning

the effect of explicit teaching of metacognitive vocabulary learning strategies on recall and retention of idioms

چکیده ندارد.

Reinforcement learning of dynamic motor sequence: learning to stand up

I n this paper, we propose a learning method f o r implementing human-like sequential movements in robots. As an example of dynamic sequential movement, we consider the “stand-up” task f o r a two-joint, three-link robot. In contrast t o the case of steady walking or standing, the desired trajectory fo r such a transient behavior is very dificult t o derive. The goal of the task is to find a pa...

Reinforcement Learning Based PID Control of Wind Energy Conversion Systems

In this paper an adaptive PID controller for Wind Energy Conversion Systems (WECS) has been developed. Theadaptation technique applied to this controller is based on Reinforcement Learning (RL) theory. Nonlinearcharacteristics of wind variations as plant input, wind turbine structure and generator operational behaviordemand for high quality adaptive controller to ensure both robust stability an...

Operation Scheduling of MGs Based on Deep Reinforcement Learning Algorithm

: In this paper, the operation scheduling of Microgrids (MGs), including Distributed Energy Resources (DERs) and Energy Storage Systems (ESSs), is proposed using a Deep Reinforcement Learning (DRL) based approach. Due to the dynamic characteristic of the problem, it firstly is formulated as a Markov Decision Process (MDP). Next, Deep Deterministic Policy Gradient (DDPG) algorithm is presented t...