Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning

2 code implementations • 20 Oct 2020 • Vaisakh Shaj, Philipp Becker, Dieter Buchler, Harit Pandya, Niels van Duijkeren, C. James Taylor, Marc Hanheide, Gerhard Neumann

We adopt a recent probabilistic recurrent neural network architecture, called Re-current Kalman Networks (RKNs), to model learning by conditioning its transition dynamics on the control actions.

Friction