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Artificial Intelligence for Prosthetics - challenge solutions
[article]
2019
arXiv
pre-print
In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a given time-varying velocity vector. Top participants were invited to describe their algorithms. In this work, we describe the challenge and present thirteen solutions that used deep reinforcement learning approaches. Many solutions use similar relaxations and heuristics, such as reward shaping, frame skipping,
arXiv:1902.02441v1
fatcat:hf7xzitrhjdqfb5cfaneovlfa4