Results 181 to 190 of about 217,696 (333)

Multiobjective Environmental Cleanup with Autonomous Surface Vehicle Fleets Using Multitask Multiagent Deep Reinforcement Learning

open access: yesAdvanced Intelligent Systems, EarlyView.
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck   +4 more
wiley   +1 more source

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

open access: yesAdvanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian   +37 more
wiley   +1 more source

A Female‐Locust‐Inspired Hybrid Soft‐Stiff Robotic Digger: Mimetics and Implications for Digging Efficiency

open access: yesAdvanced Intelligent Systems, EarlyView.
Female desert locusts dig underground to lay their eggs. They displace soil, rather than removing it, to create a tunnel. We analyze burrowing dynamics and 3D kinematics and design a locust‐inspired hybrid soft–stiff robot that reproduces this mechanism. The results show the natural strategy minimizes energy, whereas alternative patterns raise costs up
Shai Sonnenreich   +2 more
wiley   +1 more source

The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer. [PDF]

open access: yesDyn Games Appl, 2022
Wölfl B   +7 more
europepmc   +1 more source

Knowledge Sharing Research of Auto Parts Industry’s Supply Chain Based on Evolutionary Game Theory [PDF]

open access: diamond, 2015
Yunfu Huo   +5 more
openalex   +1 more source

Human‐Machine Mutual Trust Based Shared Control Framework for Intelligent Vehicles

open access: yesAdvanced Intelligent Systems, EarlyView.
This work introduces a bidirectional‐trust‐driven shared control framework for human‐machine co‐driving. The method models human‐to‐machine trust from intention discrepancies and Bayesian skill assessment, and machine‐to‐human trust from integrated ability evaluation.
Zhishuai Yin   +4 more
wiley   +1 more source

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