We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems MAS's in noisy environme...
David Wolpert, Sergey Kirshner, Christopher J. Mer...
Collecting, analyzing, and sharing information via a hypertext results in the continuous modification of information content over a long period of time. Such tasks will benefit fr...
1 We present a functional data analysis (FDA) based method to statistically model continuous signs of the American Sign Language (ASL) for use in the recognition of signs in contin...