Abstract. This paper reconsiders the deployment of synchronous optical networks (SONET), an optimization problem naturally expressed in terms of set variables. Earlier approaches, ...
Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
— We present an algorithm that probabilistically covers a bounded region of the state space of a nonlinear system with a sparse tree of feedback stabilized trajectories leading t...
- Many exciting, emerging applications require that a group of agents share a coherent view of the world given spatial distribution, incomplete and uncertain sensors, and communica...
Robin Glinton, Katia P. Sycara, David Scerri, Paul...