Benchmarking reinforcement learning algorithms on real-world robots

Reinforcement learning research with physical robots faces substantial resistance due to the lack of benchmark tasks and supporting source code. In this work, we introduce several reinforcement learning tasks with multiple commercially available robots that present varying levels of learning difficulty, setup, and repeatability. 

Reinforcement learning beat games such as Backgammon and Go, and is paving a path for smarter robots

From Go to Dota 2 to the operation of commercial HVAC systems - reinforcement learning modeling and algorithms are changing how engineers see complicated dynamical systems as games, and learn strategies to play them well. Kindred is applying the revolutionary technology that powered AlphaGo to the creation of a new generation of intelligent robotics for material handling.

Differences in interaction patterns and perception for teleoperated and autonomous humanoid robots

As the linguistic capabilities of interactive robots advance, it becomes increasingly important to understand how humans will instruct robots through natural language. What is more, with the increased use of teleoperated humanoid robots, it is important to recognize whether any differences between instructions given to humans and robots are due to the physical embodiment or perceived autonomy of the instructee. In this paper, we present the results of a human-subject experiment in which participants interacted in a collaborative, task-based setting with both a human and a suit-based, teleoperated humanoid robot said to be either autonomous or teleoperated.