Learning Hierarchical Acquisition Functions for Bayesian Optimization
Nils Rottmann,Tjaša Kunavar,Jan Babič,Jan Peters,Elmar Rueckert,Nils Rottmann,Tjaša Kunavar,Jan Babič,Jan Peters,Elmar Rueckert
Learning control policies in robotic tasks requires a large number of interactions due to small learning rates, bounds on the updates or unknown constraints. In contrast humans can infer protective and safe solutions after a single failure or unexpected observation. In order to reach similar performance, we developed a hierarchical Bayesian optimization algorithm that replicates the cognitive infe...
