We study an approach for performing concurrent activities in Markov decision processes (MDPs) based on the coarticulation framework. We assume that the agent has multiple degrees ...
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
— The Mobile Robot Programming Laboratory course has been taught at Carnegie Mellon University for the past twelve years. It is a problem-driven class designed for students with ...
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
RUPART1 is a hybrid robot control system for navigating a real-world, academic building. Hybrid robot control systems provide robust low-level navigation together with strategic p...