Deep reinforcement learning for cyber security
The scale of Internet-connected systems has increased considerably, and these systems are
being exposed to cyberattacks more than ever. The complexity and dynamics of …
being exposed to cyberattacks more than ever. The complexity and dynamics of …
Evaluation of socially-aware robot navigation
As mobile robots are increasingly introduced into our daily lives, it grows ever more
imperative that these robots navigate with and among people in a safe and socially …
imperative that these robots navigate with and among people in a safe and socially …
USV formation and path-following control via deep reinforcement learning with random braking
Y Zhao, Y Ma, S Hu - IEEE Transactions on Neural Networks …, 2021 - ieeexplore.ieee.org
This article addresses the problem of path following for underactuated unmanned surface
vessels (USVs) formation via a modified deep reinforcement learning with random braking …
vessels (USVs) formation via a modified deep reinforcement learning with random braking …
Challenges and opportunities in deep reinforcement learning with graph neural networks: A comprehensive review of algorithms and applications
Deep reinforcement learning (DRL) has empowered a variety of artificial intelligence fields,
including pattern recognition, robotics, recommendation systems, and gaming. Similarly …
including pattern recognition, robotics, recommendation systems, and gaming. Similarly …
Collision-avoiding flocking with multiple fixed-wing UAVs in obstacle-cluttered environments: a task-specific curriculum-based MADRL approach
Multiple unmanned aerial vehicles (UAVs) are able to efficiently accomplish a variety of
tasks in complex scenarios. However, developing a collision-avoiding flocking policy for …
tasks in complex scenarios. However, developing a collision-avoiding flocking policy for …
Deep reinforcement learning of collision-free flocking policies for multiple fixed-wing UAVs using local situation maps
The evolution of artificial intelligence and Internet of Things (IoT) envision a highly integrated
artificial IoT (AIoT) network. Flocking and cooperation with multiple unmanned aerial …
artificial IoT (AIoT) network. Flocking and cooperation with multiple unmanned aerial …
Intelligent motion control of unmanned surface vehicles: A critical review
MJ Er, C Ma, T Liu, H Gong - Ocean Engineering, 2023 - Elsevier
As one of the emerging tools of ocean operation, unmanned surface vehicles (USVs) have
shown great potential in ocean exploration in recent years. Motion control is an important …
shown great potential in ocean exploration in recent years. Motion control is an important …
Adaptive decision-making for automated vehicles under roundabout scenarios using optimization embedded reinforcement learning
The roundabout is a typical changeable, interactive scenario in which automated vehicles
should make adaptive and safe decisions. In this article, an optimization embedded …
should make adaptive and safe decisions. In this article, an optimization embedded …
PASCAL: population-specific curriculum-based MADRL for collision-free flocking with large-scale fixed-wing UAV swarms
Flocking with a swarm of unmanned aerial vehicles (UAVs) has been playing an important
role in various applications. However, the complexity of developing a collision-free flocking …
role in various applications. However, the complexity of developing a collision-free flocking …
知识和数据协同驱动的群体智能决策方法研究综述
蒲志强， 易建强， 刘振， 丘腾海， 孙金林， 李非墨 - 自动化学报, 2022 - aas.net.cn
群体智能(Collectire intelligence, CI) 系统具有广泛的应用前景. 当前的群体智能决策方法主要
包括知识驱动, 数据驱动两大类, 但各自存在优缺点. 本文指出, 知识与数据协同驱动将为群体 …
包括知识驱动, 数据驱动两大类, 但各自存在优缺点. 本文指出, 知识与数据协同驱动将为群体 …