Dear Editor, Underwater distributed antenna systems (DAS) are stationary infrastructures consisting of multiple geographically elements (DAEs) which interconnected through high-rate backbone networks [1]. Compared to centralized systems, the DAS could provide a larger coverage area and higher throughput for underwater acoustic (UWA) transmissions. In this work, exploiting low sound speed in wat...

Energy and thermal management is a crucial element in Formula-E race strategy development. In this study, the race-level development formulated into Markov decision process (MDP) problem featuring hybrid-type action space. Deep Deterministic Policy Gradient (DDPG) reinforcement learning implemented under distributed architecture Ape-X integrated with prioritized experience replay reward shaping...

A common situation arising in flow shops is that the job processing order must be same on each machine; this referred to as a permutation shop scheduling problem (PFSSP). Although many algorithms have been designed solve PFSSPs, machine availability typically ignored. Healthy conditions are essential for production process, which can ensure productivity and quality; thus, deteriorating effects ...

This paper presents the application of fuzzy-neuroevolutionary hybrid system with online reinforcement learning for intelligent road traffic management and control. Taking a step away from the conventional traffic control system, the hybrid system presents different methodologies in knowledge acquisition, decisionmaking, learning and goal formulation with the use of a three-layered hierarchical...

Abstract Time-domain astronomy is an active research area now, which requires frequent observations of the whole sky to capture celestial objects with temporal variations. In optical band, several telescopes in different locations could form a distributed telescope array images continuously. However, there are millions observe each night, and only limited be used for observation. Besides, obser...

In meteorological and electric power Internet of Things scenarios, in order to extend the service life relevant facilities reduce cost emergency repair, intelligent inspection swarm is introduced cooperate with monitoring tasks, which collect process current scene data through a variety sensors cameras, complete tasks such as handling fault inspection. Due limitation computing resources battery...

The paper studies the highly prototypical Fictitious Play (FP) algorithm, as well as a broad class of learning processes based on best-response dynamics, that we refer to as FP-type algorithms. A well-known shortcoming of FP is that, while players may learn an equilibrium strategy in some abstract sense, there are no guarantees that the period-by-period strategies generated by the algorithm act...

Groups of agents following fixed behavioral rules can be limited in performance and efficiency. Adaptability and flexibility are key components of intelligent behavior which allow agent groups to improve performance in a given domain using prior problem solving experience. We motivate the usefulness of individual learning by group members in the context of overall group behavior. In particular,...