Multi-agent deep reinforcement learning for multi-robot applications: A survey
J Orr, A Dutta - Sensors, 2023 - mdpi.com
Deep reinforcement learning has produced many success stories in recent years. Some
example fields in which these successes have taken place include mathematics, games …
example fields in which these successes have taken place include mathematics, games …
Hierarchical multi-robot navigation and formation in unknown environments via deep reinforcement learning and distributed optimization
L Chang, L Shan, W Zhang, Y Dai - Robotics and Computer-Integrated …, 2023 - Elsevier
Compared with a single robot, Multi-robot Systems (MRSs) can undertake more challenging
tasks in complex scenarios benefiting from the increased transportation capacity and fault …
tasks in complex scenarios benefiting from the increased transportation capacity and fault …
Safe multi-agent reinforcement learning for formation control without individual reference targets
In recent years, formation control of unmanned vehicles has received considerable interest,
driven by the progress in autonomous systems and the imperative for multiple vehicles to …
driven by the progress in autonomous systems and the imperative for multiple vehicles to …
From multi-agent to multi-robot: A scalable training and evaluation platform for multi-robot reinforcement learning
Multi-agent reinforcement learning (MARL) has been gaining extensive attention from
academia and industries in the past few decades. One of the fundamental problems in …
academia and industries in the past few decades. One of the fundamental problems in …
Hierarchical reinforcement learning with opponent modeling for distributed multi-agent cooperation
Many real-world applications can be formulated as multi-agent cooperation problems, such
as network packet routing and coordination of autonomous vehicles. The emergence of …
as network packet routing and coordination of autonomous vehicles. The emergence of …
High Efficiency Spam Filtering: A Manifold Learning‐Based Approach
C Wang, Q Li, T Ren, X Wang… - Mathematical problems in …, 2021 - Wiley Online Library
Spam filtering, which refers to detecting unsolicited, unwanted, and virus‐infested emails, is
a significant problem because spam emails lead to unnecessary costs of Internet resources …
a significant problem because spam emails lead to unnecessary costs of Internet resources …
Microservice security framework for IoT by mimic defense mechanism
F Ying, S Zhao, H Deng - Sensors, 2022 - mdpi.com
Containers and microservices have become the most popular method for hosting IoT
applications in cloud servers. However, one major security issue of this method is that if a …
applications in cloud servers. However, one major security issue of this method is that if a …
A deep reinforcement learning environment for particle robot navigation and object manipulation
Particle robots are novel biologically-inspired robotic systems where locomotion can be
achieved collectively and robustly, but not independently. While its control is currently limited …
achieved collectively and robustly, but not independently. While its control is currently limited …
Multi-UAV Behavior-based Formation with Static and Dynamic Obstacles Avoidance via Reinforcement Learning
Formation control of multiple Unmanned Aerial Vehicles (UAVs) is vital for practical
applications. This paper tackles the task of behavior-based UAV formation while avoiding …
applications. This paper tackles the task of behavior-based UAV formation while avoiding …
Language-Guided Pattern Formation for Swarm Robotics with Multi-Agent Reinforcement Learning
This paper explores leveraging the vast knowledge encoded in Large Language Models
(LLMs) to tackle pattern formation challenges for swarm robotics systems. A new framework …
(LLMs) to tackle pattern formation challenges for swarm robotics systems. A new framework …