Online BayesSim for Combined Simulator Parameter Inference and Policy Improvement
Rafael Possas,Lucas Barcelos,Rafael Oliveira,Dieter Fox,Fabio Ramos,Rafael Possas,Lucas Barcelos,Rafael Oliveira,Dieter Fox,Fabio Ramos
Recent advancements in Bayesian likelihood-free inference enables a probabilistic treatment for the problem of estimating simulation parameters and their uncertainty given sequences of observations. Domain randomization can be performed much more effectively when a posterior distribution provides the correct uncertainty over parameters in a simulated environment. In this paper, we study the integr...
