The routing in communication networks is typically a multicriteria decision making (MCDM) problem. However, setting the parameters of most used MCDM methods to fit the preferences ...
Abstract— Least-squares policy iteration is a useful reinforcement learning method in robotics due to its computational efficiency. However, it tends to be sensitive to outliers...
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...
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
As knowledge becomes the primary focus of work in many industries, virtual communities and groups are emerging as part of new organizational forms. Within these virtual forms, eff...