With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …

In recent years, the interest in leveraging quantum effects for enhancing machine learning
tasks has significantly increased. Many algorithms speeding up supervised and …

Computation offloading from a mobile device to the edge server is an emerging paradigm to
reduce completion latency of intensive computations in mobile-edge computing (MEC). In …

Bayesian reward learning from demonstrations enables rigorous safety and uncertainty
analysis when performing imitation learning. However, Bayesian reward learning methods …

Real-time remote estimation is critical for mission-critical applications including industrial
automation, smart grid and tactile Internet. In this paper, we propose a hybrid automatic …

We propose a novel randomized linear programming algorithm for approximating the
optimal policy of the discounted-reward and average-reward Markov decision problems. By …

This study investigates the optimization problem of an infinite stage discrete time Markov
decision process (MDP) with a long‐run average metric considering both mean and …

Real-time wireless networked control of an Autonomous Guided Vehicle (AGV) from an
edge cloud controller is an attractive approach to reduce hardware costs of AGVs, eg, for …

This work proposes a two-level hierarchical constrained control structure for reinforcement
learning (RL) with application in a Primary Separation Vessel (PSV). The lower level is …

Planning is useful. It lets people take actions that have desirable long-term consequences.
But, planning is hard. It requires thinking about consequences, which consumes limited …