Abstract— Learning inverse kinematics has long been fascinating the robot learning community. While humans acquire this transformation to complicated tool spaces with ease, it is...
We present PLIANT, a learning system that supports adaptive assistance in an open calendaring system. PLIANT learns user preferences from the feedback that naturally occurs during...
Melinda T. Gervasio, Michael D. Moffitt, Martha E....
In the absence of explicit queries, an alternative is to try to infer users' interests from implicit feedback signals, such as clickstreams or eye tracking. The interests, fo...
As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
—Due to the difficulty and thus effort and expenses involved in creating them, personalization strategies in learning environments have to demonstrate a higher returnon-investmen...