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end-to-end-guided-rl-using-online-learning's Introduction

End-to-End-Guided-RL-using-Online-Learning

Designed a Novel End to End algorithm with Reinforcement Learning guided by Online Learning to MPC(Model Predictive Control), leading to optimal policies for continuous control tasks.

Simulation results: Control Task is to Swingup and Balance the pole:

a)Control of Cartpole with Augmented Random Search(a Model Free RL):
Pole Fails to stay in the upright position after swingup using ARS alone

b)Control of Cartpole with Augmented Random Search + Online Learning MPC:
Pole balances forever, online Learning guides the Augmented Random Search (RL policy)

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