Autonomous Navigation for eVTOL: Review and Future Perspectives
H Wei, B Lou, Z Zhang, B Liang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This survey paper explores the emergent domain of electric vertical takeoff and landing
vehicles (eVTOLs), emphasizing the critical role of autonomous navigation capabilities …
vehicles (eVTOLs), emphasizing the critical role of autonomous navigation capabilities …
A Survey of Progress on Cooperative Multi-agent Reinforcement Learning in Open Environment
Multi-agent Reinforcement Learning (MARL) has gained wide attention in recent years and
has made progress in various fields. Specifically, cooperative MARL focuses on training a …
has made progress in various fields. Specifically, cooperative MARL focuses on training a …
Robust Wind-Resistant Hovering Control of Quadrotor UAVs Using Deep Reinforcement Learning
Unmanned Aerial Vehicles (UAVs) have extensive applications such as logistics
transportation and aerial photography. However, UAVs are sensitive to winds. Traditional …
transportation and aerial photography. However, UAVs are sensitive to winds. Traditional …
Decentralized Robust V-learning for Solving Markov Games with Model Uncertainty
The Markov game is a popular reinforcement learning framework for modeling competitive
players in a dynamic environment. However, most of the existing works on Markov games …
players in a dynamic environment. However, most of the existing works on Markov games …
SQIX: QMIX Algorithm Activated by General Softmax Operator for Cooperative Multiagent Reinforcement Learning
M Zhang, W Tong, G Zhu, X Xu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Multiagent cooperative systems can be used to conceptualize many real-world problems.
Reinforcement learning is a particularly effective tool. The issue of bias in-function value …
Reinforcement learning is a particularly effective tool. The issue of bias in-function value …
Multiagent Reinforcement Learning: Methods, Trustworthiness, Applications in Intelligent Vehicles, and Challenges
Multiagent Reinforcement Learning (MARL) plays a pivotal role in intelligent vehicle
systems, offering solutions for complex decision-making, coordination, and adaptive …
systems, offering solutions for complex decision-making, coordination, and adaptive …
Group Multirole Assignment With Cooperation, Conflict, and Public Interest Factors
X Ke, H Zhu, D Liu - IEEE Transactions on Computational …, 2024 - ieeexplore.ieee.org
In collaborative endeavors, there are always various types of cooperation, conflict, and
public interest relationships. Taking home appliance production as a typical example, this …
public interest relationships. Taking home appliance production as a typical example, this …
Multiagent Reinforcement Learning for Active Guidance Control of Railway Vehicles with Independently Rotating Wheels
J Wei, Z Lu, Z Yin, Z Jing - Applied Sciences, 2024 - mdpi.com
This paper presents a novel data-driven multiagent reinforcement learning (MARL)
controller for enhancing the running stability of independently rotating wheels (IRW) and …
controller for enhancing the running stability of independently rotating wheels (IRW) and …
Reinforcement Learning Driven Cooperative Ball Balance in Rigidly Coupled Drones
S Barawkar, N Chopra - arXiv preprint arXiv:2404.19070, 2024 - arxiv.org
Multi-drone cooperative transport (CT) problem has been widely studied in the literature.
However, limited work exists on control of such systems in the presence of time-varying …
However, limited work exists on control of such systems in the presence of time-varying …
Combination of Density-Based Spatial Clustering of Applications with Noise Method with Grid Search to Improve Complexity Using Nash Equilibrium
U Kazemi, S Soleimani - 2024 - researchsquare.com
One of the important issues in data processing is clustering, the purpose of which is to find
similar patterns in the data. Many clustering methods differ in their approaches and …
similar patterns in the data. Many clustering methods differ in their approaches and …