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...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser: Van De Meent, J, Paige, B, Tolpin, D, Wood, F
Format: Conference item
Veröffentlicht: Journal of Machine Learning Research 2016