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Tracking Control for a Spherical Pendulum via Curriculum Reinforcement Learning
Reinforcement Learning (RL) allows learning non-trivial robot control laws purely from data.
SKID RAW: Skill Discovery from Raw Trajectories
Integrating robots in complex everyday environments requires a multitude of problems to be solved.
High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards
Robots that can learn in the physical world will be important to en-able robots to escape their stiff and pre-programmed movements.
Learning walk and trot from the same objective using different types of exploration
In quadruped gait learning, policy search methods that scale high dimensional continuous action spaces are commonly used.
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