Results 11 to 20 of about 7,724,255 (252)
The impact of exploration on convergence and performance of multi-agent Q-learning dynamics
, 2023 Understanding the impact of exploration on the behaviour of multi-agent learning has, so far, benefited from the restriction to potential, or network zero-sum games in which convergence to an equilibrium can be shown.
Hussain, A +2 more
core +5 more sources
Multi-Source Multi-Destination Hybrid Infrastructure-Aided Traffic Aware Routing in V2V/I Networks
IEEE Access, 2022 The concept of the “connected car” offers the potential for safer, more enjoyable and more efficient driving and eventually autonomous driving.
Teodor Ivanescu +3 more
doaj +1 more source
Frame Size Optimization for Dynamic Framed Slotted ALOHA in RFID Systems
Jisuanji kexue yu tansuo, 2021 In recent years, the State Grid has actively promoted the construction of ubiquitous power Internet of things, so as to realize the interconnection and optimized management of things in the power system. Specifically, radio frequency identification (RFID)
HE Jindong, BU Yanling, SHI Congcong, XIE Lei
doaj +1 more source
Cybernetics and Information Technologies, 2023 Fog computing is one of the emerging forms of cloud computing which aims to satisfy the ever-increasing computation demands of the mobile applications. Effective offloading of tasks leads to increased efficiency of the fog network, but at the same time ...
Bhargavi K. +2 more
doaj +1 more source
Applied Sciences, 2019 Programming robots for performing different activities requires calculating sequences of values of their joints by taking into account many factors, such as stability and efficiency, at the same time. Particularly for walking, state of the art techniques
Cristyan R. Gil +2 more
doaj +1 more source
Traffic Light Cycle Configuration of Single Intersection Based on Modified Q-Learning
Applied Sciences, 2019 In recent years, within large cities with a high population density, traffic congestion has become more and more serious, resulting in increased emissions of vehicles and reducing the efficiency of urban operations.
Hung-Chi Chu +3 more
doaj +1 more source
Aircraft Maintenance Check Scheduling Using Reinforcement Learning
Aerospace, 2021 This paper presents a Reinforcement Learning (RL) approach to optimize the long-term scheduling of maintenance for an aircraft fleet. The problem considers fleet status, maintenance capacity, and other maintenance constraints to schedule hangar checks ...
Pedro Andrade +3 more
doaj +1 more source
A Q-Learning Proposal for Tuning Genetic Algorithms in Flexible Job Shop Scheduling Problems
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 Genetic algorithms (GAs) belong to the category of evolutionary algorithms and are frequently utilized for resolving challenging combinatorial problems.
Christian Perez +2 more
doaj +1 more source
Nonreciprocating Sharing Methods in Cooperative Q-Learning Environments [PDF]
, 2012 Past research on multiagent simulation with cooperative reinforcement learning (RL) focuses on developing sharing strategies that are adopted and used by all agents in the environment. In this paper, we target situations where this assumption of a single
Cao, Yong, Cunningham, Bryan
core +2 more sources
Energies, 2021 In this paper, two universal reinforcement learning methods are considered to solve the problem of maximum power point tracking for photovoltaics. Both methods exhibit fast achievement of the MPP under varying environmental conditions and are applicable ...
Kostas Bavarinos +2 more
doaj +1 more source