Learning from experimentation allows a system to acquire planning domain knowledge by correcting its knowledge when an action execution fails. Experiments are designed and planned...
The ability to generate narrative is of importance to computer systems that wish to use story effectively for entertainment, training, or education. We identify two properties of ...
—To efficiently solve challenging motion-planning problems with dynamics, this paper proposes treating motion planning not just as a search problem in a continuous space but as ...
Abstract— Robotic manipulation is important for real, physical world applications. General Purpose manipulation with a robot (eg. delivering dishes, opening doors with a key, etc...
We are interested in multi-agent contracting, in which customers must solicit the resources and capabilities of other, self-interested agents in order to accomplish their goals. G...