Essential Dynamics

The essential dynamics algorithm combines ideas from the adaptive control and policy search. The resulting algorithm works in high dimensional, continuous domains. The papers below describe the algorithm, relate it to Linear Quadratic Control and Reinforcement Learning, and describe it on two tasks: a toy bicycle riding problem, and controlling a robot arm on a Segway base, which dynamically rotates.



The source code for the bicycle riding experiments.


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