Results 21 to 30 of about 1,898 (151)

About Digital Twins, agents, and multiagent systems: a cross-fertilisation journey

open access: yes, 2022
Digital Twins (DTs) are rapidly emerging as a fundamental brick of engineering cyber-physical systems, but their notion is still mostly bound to specific business domains (e.g. manufacturing), goals (e.g. product design), or application domains (e.g. the
Picone, Marco   +2 more
core   +2 more sources

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath   +4 more
wiley   +1 more source

Multiagent reinforcement learning in Markov games : asymmetric and symmetric approaches [PDF]

open access: yes, 2004
Modern computing systems are distributed, large, and heterogeneous. Computers, other information processing devices and humans are very tightly connected with each other and therefore it would be preferable to handle these entities more as agents than ...
Könönen, Ville
core  

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

open access: yesAdvanced Intelligent Discovery, EarlyView.
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang   +9 more
wiley   +1 more source

From physical models to well-founded control

open access: yes, 2009
Mobile sensors are an attractive proposition forenvironmental sensing, but pose significant engineering problems. Not leastamongst these is the need to match the behaviour of the sensor platform to thephysical environment in which it operates. We present
Mike Hinchey   +13 more
core   +2 more sources

Design, Control, and Clinical Applications of Magnetic Actuation Systems: Challenges and Opportunities

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo   +3 more
wiley   +1 more source

Beyond autonomy : the self and life of social agents

open access: yes, 2019
Agents have gained popularity nowadays as virtual assistants and companions of their human users supporting daily activities in many aspects of personal life.
Tan, Ah-Hwee, Subagdja, Budhitama
core   +1 more source

Human‐in‐the‐Loop Swarms: A Bionic Swarm Approach to Real‐World Soil Mapping

open access: yesAdvanced Intelligent Systems, EarlyView.
This article introduces the “Bionic Swarm,” a novel system that lowers the barriers to real‐world swarm validation by abstracting difficult hardware tasks to app‐guided human agents. We demonstrate the system's utility through the experimental validation of a geotechnical soil‐mapping swarm algorithm and show superior performance to baseline approaches
Petras Swissler   +5 more
wiley   +1 more source

On the benefits of argumentation-derived evidence in learning policies [PDF]

open access: yes, 2010
. Trust is a mechanism for managing the uncertainty about autonomous entities and the information they store, and so can play an important role in any decentralized system.
Parsons, Simon   +12 more
core   +1 more source

“It Is Much Safer to Be Sparse than Connected”: Safe Control of Robotic Swarm Density Dynamics with PDE Optimization with State Constraints

open access: yesAdvanced Intelligent Systems, EarlyView.
This paper proposes a novel control framework to ensure safety of a robotic swarm. A feedback optimization controller is capable of driving the swarm toward a target density while keeping risk‐zone exposure below a safety threshold. Theory and experiments show how safety is more effectively achieved for sparsely connected swarms.
Longchen Niu, Gennaro Notomista
wiley   +1 more source

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