title: Computational motor control in humans and robots.
abstract: Computational models can provide useful guidance in the design of behavioral and neurophysiological experiments and in the interpretation of complex, high dimensional biological data. Because many problems faced by the primate brain in the control of movement have parallels in robotic motor control, models and algorithms from robotics research provide useful inspiration, baseline performance, and sometimes direct analogs for neuroscience.
authors.affiliation: Computer Science, Neuroscience & Biokinesiology and Physical Therapy, University of Southern California, 3641 Watt Way, Los Angeles, CA 90089, USA. sschaal@usc.edu
authors.forename: Stefan
authors.initials: S
authors.lastname: Schaal
authors.forename: Nicolas
authors.initials: N
authors.lastname: Schweighofer
mesh_terms: D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D001921:Brain / Q000502:physiology; D003201:Computers; D006801:Humans; D007858:Learning / Q000502:physiology; D008959:Models, Neurological; D009068:Movement / Q000502:physiology*; D012371:Robotics; D013269:Stochastic Processes