Electric Vehicle Charging Guidance Algorithm Based on Informer Multi‐Agent Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2025 at "International Journal of Robust and Nonlinear Control"
DOI: 10.1002/rnc.70254
Abstract: With the vigorous development of the electric vehicle (EV) industry, the demand for charging has surged. However, the relative lag in the construction of charging infrastructure has led to a series of problems for drivers,… read more here.
Keywords: guidance; multi agent; agent reinforcement; informer ... See more keywords
Multi-agent reinforcement learning based on local communication
Sign Up to like & getrecommendations! Published in 2018 at "Cluster Computing"
DOI: 10.1007/s10586-018-2597-x
Abstract: Aiming at the locality and uncertainty of observations in large-scale multi-agent application scenarios, the model of Decentralized Partially Observable Markov Decision Processes (DEC-POMDP) is considered, and a novel multi-agent reinforcement learning algorithm based on local… read more here.
Keywords: agent; reinforcement learning; multi agent; local communication ... See more keywords
Toward finding strong pareto optimal policies in multi-agent reinforcement learning
Sign Up to like & getrecommendations! Published in 2024 at "Machine Learning"
DOI: 10.1007/s10994-024-06700-1
Abstract: In this work, we study the problem of finding Pareto optimal policies in multi-agent reinforcement learning problems with cooperative reward structures. We show that any algorithm where each agent only optimizes their reward is subject… read more here.
Keywords: pareto; multi agent; agent reinforcement; reinforcement learning ... See more keywords
An efficient routing access method based on multi-agent reinforcement learning in UWSNs
Sign Up to like & getrecommendations! Published in 2022 at "Wireless Networks"
DOI: 10.1007/s11276-021-02838-1
Abstract: A large proportion of underwater data is collected in deep sea. Compared with the direct bottom-to-surface acoustic links, underwater sensor networks (UWSNs) with hierarchical network model topology are more efficient at transmitting huge amounts of… read more here.
Keywords: multi agent; agent reinforcement; reinforcement learning; method ... See more keywords
MRL-SCSO: Multi-agent Reinforcement Learning-Based Self-Configuration and Self-Optimization Protocol for Unattended Wireless Sensor Networks
Sign Up to like & getrecommendations! Published in 2017 at "Wireless Personal Communications"
DOI: 10.1007/s11277-016-3729-3
Abstract: Resource-constrained nodes in unattended wireless sensor network (UWSN) operate in a hostile environment with less human intervention. Achieving the optimal quality of service (QoS) in terms of packet delivery ratio, delay, energy, and throughput is… read more here.
Keywords: multi agent; topology; unattended wireless; agent reinforcement ... See more keywords
Grandmaster level in StarCraft II using multi-agent reinforcement learning
Sign Up to like & getrecommendations! Published in 2019 at "Nature"
DOI: 10.1038/s41586-019-1724-z
Abstract: Many real-world applications require artificial agents to compete and coordinate with other agents in complex environments. As a stepping stone to this goal, the domain of StarCraft has emerged as an important challenge for artificial… read more here.
Keywords: reinforcement learning; multi agent; agent reinforcement; grandmaster level ... See more keywords
A Novel and Efficient Influence-Seeking Exploration in Deep Multi-Agent Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3171053
Abstract: Although recent years witnessed notable success for a cooperative setting in multi-agent reinforcement learning (MARL), efficient explorations are still challenging primarily due to the complex dynamics of inter-agent interactions constituting the high dimension of action… read more here.
Keywords: agent reinforcement; influence; action; exploration ... See more keywords
Real-Time Multi-Vehicle Scheduling in Tasks With Dependency Relationships Using Multi-Agent Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3399610
Abstract: With the advancement of technology in vehicle-road collaboration and autonomous driving, new commercial applications have surfaced. These include autonomous ride-hailing vehicles and unmanned delivery vehicles. As a result of the challenges presented by commercial applications,… read more here.
Keywords: real time; multi; multi agent; agent reinforcement ... See more keywords
Deployment of Unmanned Aerial Vehicles in Next-Generation Wireless Communication Network Using Multi-Agent Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3401016
Abstract: To address the challenges posed by a large number of disaster-waiver-affected users and the complexities of scaling centralized algorithms for rapidly restoring emergency communication services, the paper proposes a distributed intent-based optimization architecture based on… read more here.
Keywords: reinforcement; multi agent; agent reinforcement; network ... See more keywords
Rethinking Exploration and Experience Exploitation in Value-Based Multi-Agent Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3530974
Abstract: Cooperative Multi-Agent Reinforcement Learning (MARL) focuses on developing strategies to effectively train multiple agents to learn and adapt policies collaboratively. Despite being a relatively new area of research, most MARL methods are based on well-established… read more here.
Keywords: exploitation; exploration; multi agent; agent reinforcement ... See more keywords
Communication-Aware Graph Neural Network for Multi-Agent Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3554736
Abstract: Multi-agent reinforcement learning (MARL) requires effective communication strategies to solve complex control tasks over uncertain communication channels. This paper explores a communication-aware graph neural network (GNN) approach for MARL, where the interactions between agents are… read more here.
Keywords: aware graph; multi agent; agent reinforcement; reinforcement learning ... See more keywords