Results 21 to 30 of about 36,270,661 (145)
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
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
Welcome to AAMAS 2022, the 21st edition of the International Conference on Autonomous Agents and Multiagent Systems! AAMAS gathers researchers and practitioners from around the world to share and discuss the latest advances in the field of autonomous ...
core +1 more source
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
Human‐in‐the‐Loop Swarms: A Bionic Swarm Approach to Real‐World Soil Mapping
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
Multiagent reinforcement learning in Markov games : asymmetric and symmetric approaches [PDF]
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 +1 more source
Dynamic Obstacle Avoidance of Metamorphic Microrobots Using Concentric Sector Navigator
Metamorphic magnetic microrobots are navigated using a concentric sector navigator for dynamic obstacle avoidance in both microroller and swarm states. After microroller transport, citrate‐triggered dissolution releases nanoparticles that reassemble into a controllable swarm.
Zhaowen Su +4 more
wiley +1 more source
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha +2 more
wiley +1 more source
Do (and say) as I say: Linguistic adaptation in human-computer dialogs [PDF]
© Theodora Koulouri, Stanislao Lauria, and Robert D. Macredie. This article has been made available through the Brunel Open Access Publishing Fund.There is strong research evidence showing that people naturally align to each other’s vocabulary, sentence ...
Macredie, R, Kolouri, T, Lauria, S
core +1 more source
Efficacy, safety and cost‐effectiveness of CAR‐T therapy
CAR T‐cells demonstrate high efficacy in blood cancers, including ALL, MM and DLBCL. Innovations target solid tumours despite challenges such as antigen escape. Combination therapies enhance the delivery and infiltration of CAR T cells. Toxicity, cost and resistance remain major barriers to clinical use.
Emina Karahmet Sher +7 more
wiley +1 more source

