Results 11 to 20 of about 37,633,914 (99)
Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer +3 more
wiley +1 more source
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 cooperation for solving global optimization problems: an extendible framework with example cooperation strategies [PDF]
This paper proposes the use of multiagent cooperation for solving global optimization problems through the introduction of a new multiagent environment, MANGO.
Günay, Akın +6 more
core +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
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
The Collective Power of Bacteria as a Blueprint for Emergent Intelligence
Small cells, powerful collectives. Bacteria demonstrate how sophisticated behaviors can emerge from many simple individuals working together. We explore the remarkable world of bacterial communities and the mechanisms that underpin their complex emergent behaviors, enabling impressive adaptability, robustness, and responsiveness to changing ...
Johanna A. Blee +2 more
wiley +1 more source
A Scalable Multiagent Platform for Large Systems [PDF]
[EN] A new generation of open and dynamic systems requires execution frameworks that are capable of being efficient and scalable when large populations of agents are launched.
Vicent Botti +9 more
core +1 more source
Graph Neural Network‐Based Reinforcement Learning for Decentralized Multi‐Robot Manipulation
Robot arms lifting a large object face a trade‐off: centralized controllers explode in parameters, while decentralized ones cannot coordinate. A GNN resolves this—each arm runs its own network but acts on the full team state, achieving centralized‐level coordination with decentralized execution. Trained across team sizes, a single policy scales to four‐
Tong Chen +3 more
wiley +1 more source
Supply Chain Management and Multiagent Systems: An Overview
This chapter introduces the topic of this book by presenting the fields of supply chain management, multiagent systems, and the merger of these two fields into multiagent-based supply chain management.
Thierry Moyaux +5 more
core +1 more source
From Instruction to Inheritance: Scaling Robot Learning Through Knowledge Circulation
Robot learning moves from one‐way instruction toward knowledge circulation. Humans teach robots, robots teach one another, and robots share acquired skills with humans. This perspective connects teaching, embodiment, and learning architectures to explore how knowledge is inherited, adapted, and enriched across agents, opening a path toward scalable ...
Kento Kawaharazuka +13 more
wiley +1 more source

