Quo vadis artificial intelligence?
The study of artificial intelligence (AI) has been a continuous endeavor of scientists and
engineers for over 65 years. The simple contention is that human-created machines can do …
engineers for over 65 years. The simple contention is that human-created machines can do …
Deep reinforcement learning based mobile robot navigation: A review
K Zhu, T Zhang - Tsinghua Science and Technology, 2021 - ieeexplore.ieee.org
Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement
Learning (DRL) has received significant attention because of its strong representation and …
Learning (DRL) has received significant attention because of its strong representation and …
A review of cooperative multi-agent deep reinforcement learning
A Oroojlooy, D Hajinezhad - Applied Intelligence, 2023 - Springer
Abstract Deep Reinforcement Learning has made significant progress in multi-agent
systems in recent years. The aim of this review article is to provide an overview of recent …
systems in recent years. The aim of this review article is to provide an overview of recent …
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 …
Graph neural networks for decentralized multi-robot path planning
Effective communication is key to successful, decentralized, multi-robot path planning. Yet, it
is far from obvious what information is crucial to the task at hand, and how and when it must …
is far from obvious what information is crucial to the task at hand, and how and when it must …
Mobile robot path planning in dynamic environments through globally guided reinforcement learning
Path planning for mobile robots in large dynamic environments is a challenging problem, as
the robots are required to efficiently reach their given goals while simultaneously avoiding …
the robots are required to efficiently reach their given goals while simultaneously avoiding …
Message-aware graph attention networks for large-scale multi-robot path planning
The domains of transport and logistics are increasingly relying on autonomous mobile
robots for the handling and distribution of passengers or resources. At large system scales …
robots for the handling and distribution of passengers or resources. At large system scales …
PRIMAL: Pathfinding Via Reinforcement and Imitation Multi-Agent Learning - Lifelong
Multi-agent path finding (MAPF) is an indispensable component of large-scale robot
deployments in numerous domains ranging from airport management to warehouse …
deployments in numerous domains ranging from airport management to warehouse …
A critical review of communications in multi-robot systems
Abstract Purpose of Review This review summarizes the broad roles that communication
formats and technologies have played in enabling multi-robot systems. We approach this …
formats and technologies have played in enabling multi-robot systems. We approach this …
Graph neural networks: Architectures, stability, and transferability
Graph neural networks (GNNs) are information processing architectures for signals
supported on graphs. They are presented here as generalizations of convolutional neural …
supported on graphs. They are presented here as generalizations of convolutional neural …