Black-box policy search with probabilistic programs

In this work we show how to represent policies as programs: that is, as stochastic simulators with tunable parameters. To learn the parameters of such policies we develop connections between black box variational inference and existing policy search approaches. We then explain how such learning can...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Van De Meent, J, Paige, B, Tolpin, D, Wood, F
Format: Conference item
Wydane: Journal of Machine Learning Research 2016