Results 121 to 130 of about 10,350,910 (281)

Multi-Agent Deep Reinforcement Learning Framework for Efficient Aerial Wildfire Fighting

Engineering Proceedings
The increasing severity of global wildfires requires advanced suppression strategies to mitigate impacts on the environment and human life. This work investigates the applicability of Multi-Agent Reinforcement Learning (MARL) to aerial wildfire ...
Leonard Bardtke, Nabih Naeem, Nikolaos Kalliatakis, Prajwal Shiva Prakasha, Thomas Clemen   +4 more
doaj   +1 more source

3D Printing of Self‐Healing Polymers by Material Extrusion: A Process‐Centric Review of Setups, Parameters, and Applications

Advanced Robotics Research, EarlyView.
This review highlights recent advances in material extrusion 3D printing of self‐healing polymers, focusing on the interplay between material chemistry, rheology, hardware customization, and process optimization. Filament‐ and ink‐based extrusion strategies, multimaterial architectures, and postprocessing approaches are discussed for applications in ...
Antonio Pavone, Gianni Stano, Gianluca Percoco   +2 more
wiley   +1 more source

Multi‐agent track confirmation utilising reinforcement learning and game theoretics

IET Radar, Sonar & Navigation
This research investigates the problem of track conformation for a search and evade challenge within the context of the radar resource management domain.
Geoffrey Dolinger, Timothy Sharp, Bryan Lavender, Alexander Stringer, Joseph Karch, Adam Bowersox, Justin Metcalf   +6 more
doaj   +1 more source

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

Nonreciprocal Swarmalators With Reconfigurable and Controllable Formations for Robot Collectives

Advanced Robotics Research, EarlyView.
Nonreciprocal swarmalator interactions are enabled through control barrier functions to transform self‐organizing robot collectives into reconfigurable, constraint‐aware systems. Complex two‐ and three‐dimensional shapes, continuous morphing, obstacle‐aware navigation, collective splitting, and object transport emerge from modulating agent‐level ...
Kush Patel, Xinyue Xu, Wei Xiao, Steven Ceron   +3 more
wiley   +1 more source

Learning graph based individual intrinsic reward for multi-agent reinforcement learning

ICT Express
Designing a reward function is a critical challenge in reinforcement learning. However, as environments become more complex and tasks grow more difficult, designing a reward function that drives optimal behavior becomes increasingly challenging.
Seokhun Ju, Seungyub Han, Taehyun Cho, Jungwoo Lee, Taeyoung Lee, Minkyoung Kim, Jinho An   +6 more
doaj   +1 more source

Preprint: AGMARL-DKS: An Adaptive Graph-Enhanced Multi-Agent Reinforcement Learning for Dynamic Kubernetes Scheduling

State-of-the-art cloud-native applications require intelligent schedulers that can effectively balance system stability, resource utilisation, and associated costs. While Kubernetes provides feasibility-based placement by default, recent research efforts
Hamed Hamzeh
core   +1 more source

Magnetically Actuated Microrobot for Drug Delivery: Current Progress and Challenges

Advanced Robotics Research, EarlyView.
Magnetically actuated microrobots are reshaping targeted drug delivery through wireless propulsion, programmable materials, and localized therapeutic release. This review examines how fabrication, body material selection, structural architecture, loading mechanisms, and imaging‐guided control converge to enable microrobotic therapies while identifying ...
Yang Yang, David J. Cappelleri
wiley   +1 more source

A Deep Reinforcement Learning-Based Cooperative Guidance Strategy Under Uncontrollable Velocity Conditions

Aerospace
We present a novel approach to generating a cooperative guidance strategy using deep reinforcement learning to address the challenge of cooperative multi-missile strikes under uncontrollable velocity conditions.
Hao Cui, Ke Zhang, Minghu Tan, Jingyu Wang   +3 more
doaj   +1 more source

Concept Learning for Cooperative Multi-Agent Reinforcement Learning

2025 IEEE 26th China Conference on System Simulation Technology and its Applications (CCSSTA)
Despite substantial progress in applying neural networks (NN) to multi-agent reinforcement learning (MARL) areas, they still largely suffer from a lack of transparency and interoperability. However, its implicit cooperative mechanism is not yet fully understood due to black-box networks.
Zhonghan Ge, Yuanyang Zhu, Chunlin Chen 0001   +2 more
openaire   +2 more sources