Applied Artificial Intelligence Lab (A2I)

The Applied AI Lab (A2I) explores core challenges in AI and Machine Learning to enable robots to robustly and effectively operate in complex, real-world environments. Our research is guided by our vision to create machines which constantly improve through use in their dedicated workspace. In doing so we explore a number of intellectual challenges at the heart of robot learning such as machine introspection in perception and decision making, data efficient learning from demonstration, task-based and transfer learning and the learning of complex tasks via a curriculum of less complex ones. All the while our intellectual curiosity remains grounded in real-world robotics domains such as autonomous driving, logistics, manipulation or space exploration.
RT @IngmarPosner: Hugely excited to be leading this with so many great partners and colleagues involved. Starting 2021... @a2i_oxford @oxfo…

RT @Alex_L_Mitchell: Interested in solving for locomotion trajectories for complex real-world robots? We find solutions via gradient descen…
RT @hawesie: We're looking to hire someone who can act as a bridge between the worlds of sequential decision making and medical imaging in…
RT @martinengelcke: Our recent work led by @Alex_L_Mitchell on quadruped locomotion is available at #iros2020 on-demand :) https://t.co/1d0…
RT @IngmarPosner: Interested in leveraging attention for robust and efficient RL? Come and see us today at #CoRL2020... https://t.co/fLR8ju…
RT @omgroth: We’re getting really excited about presenting RELATE - our latest work on object-centric generative modelling - @NeurIPSConf!…