Reinforcement Learning for High-dimensional Continuous Control in Biomechanics: An Intro to ArtiSynth-RL

Understand

Neural control is an exciting mystery which we instinctively master.

• Yet, researchers have a hard time explaining the motor control trajectories.
• Physiologically accurate biomechanical simulations can, to some extent, mimic live subjects and help us form evidence-based hypotheses.
• In these simulated environments, muscle excitations are typically calculated through inverse dynamic optimizations which do not possess a closed-form solution.