Genewein T, Braun DA (2103) Bayesian Occam’s Razor for structure selection in human motor learning. RSS 2013 Workshop on Hierarchical and Structured Learning for Robotics, Berlin.
I presented my poster on “Bayesian Occam’s Razor for structure selection in human motor learning” at the Workshop on Hierarchical and Structured Learning for Robotics which was part of RSS2013 in Berlin. On the poster we investigate Bayesian model selection as the answer to the question of how to select among several learned structures. In particular, we designed a sensorimotor experiment in virtual reality that investigates whether human model selection behavior is quantitatively consistent with Bayesian model selection - in particular whether humans are in line with Occam’s razor and prefer the simpler model if two models explain the observed data equally well.
More on the work presented on the poster and the results can be found here.