no code implementations • • Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Davide Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin Riedmiller
There is a widespread intuition that model-based control methods should be able to surpass the data efficiency of model-free approaches.
This paper sets out to disambiguate the role of different design choices for learning dynamics models, by comparing their performance to planning with a ground-truth model -- the simulator.
no code implementations • 18 Nov 2020 • Tom Ward, Andrew Bolt, Nik Hemmings, Simon Carter, Manuel Sanchez, Ricardo Barreira, Seb Noury, Keith Anderson, Jay Lemmon, Jonathan Coe, Piotr Trochim, Tom Handley, Adrian Bolton
In the pursuit of artificial general intelligence, our most significant measurement of progress is an agent's ability to achieve goals in a wide range of environments.
The dm_control software package is a collection of Python libraries and task suites for reinforcement learning agents in an articulated-body simulation.
Invariances to translation, rotation and other spatial transformations are a hallmark of the laws of motion, and have widespread use in the natural sciences to reduce the dimensionality of systems of equations.