Zobrazeno 1 - 10
of 119 674
pro vyhledávání: '"Multi-agent System"'
Autor:
Bachtis, Dimitrios
We introduce a $\phi^{4}$ lattice field theory with frustrated dynamics as a multi-agent system to reproduce stylized facts of financial markets such as fat-tailed distributions of returns and clustered volatility. Each lattice site, represented by a
Externí odkaz:
http://arxiv.org/abs/2411.15813
This project, named HEnRY, aims to introduce a Multi-Agent System (MAS) into Intesa Sanpaolo. The name HEnRY summarizes the project's core principles: the Hierarchical organization of agents in a layered structure for efficient resource management; E
Externí odkaz:
http://arxiv.org/abs/2410.12720
Autor:
Su, Haoyang, Chen, Renqi, Tang, Shixiang, Zheng, Xinzhe, Li, Jingzhe, Yin, Zhenfei, Ouyang, Wanli, Dong, Nanqing
The rapid advancement of scientific progress requires innovative tools that can accelerate discovery. While recent AI methods, particularly large language models (LLMs), have shown promise in tasks such as hypothesis generation and experimental desig
Externí odkaz:
http://arxiv.org/abs/2410.09403
Autor:
Lingxiang Wei1, Dongjun Guo1 guo_dongjun@163.com, Junyuan Ji2, Zhilong Chen1 chen-zl@vip.163.com, Huapeng Hu2, Xiaoli Peng1
Publikováno v:
Underground Space (2096-2754). Dec2024, Vol. 19, p251-278. 28p.
This study introduces "RadCouncil," a multi-agent Large Language Model (LLM) framework designed to enhance the generation of impressions in radiology reports from the finding section. RadCouncil comprises three specialized agents: 1) a "Retrieval" Ag
Externí odkaz:
http://arxiv.org/abs/2412.06828
Autor:
Laverick, Andrew, Surrao, Kristen, Zubeldia, Inigo, Bolliet, Boris, Cranmer, Miles, Lewis, Antony, Sherwin, Blake, Lesgourgues, Julien
Multi-agent systems (MAS) utilizing multiple Large Language Model agents with Retrieval Augmented Generation and that can execute code locally may become beneficial in cosmological data analysis. Here, we illustrate a first small step towards AI-assi
Externí odkaz:
http://arxiv.org/abs/2412.00431
Large Language Models (LLMs) excel in diverse applications including generation of code snippets, but often struggle with generating code for complex Machine Learning (ML) tasks. Although existing LLM single-agent based systems give varying performan
Externí odkaz:
http://arxiv.org/abs/2411.07464
Autor:
Fourney, Adam, Bansal, Gagan, Mozannar, Hussein, Tan, Cheng, Salinas, Eduardo, Erkang, Zhu, Niedtner, Friederike, Proebsting, Grace, Bassman, Griffin, Gerrits, Jack, Alber, Jacob, Chang, Peter, Loynd, Ricky, West, Robert, Dibia, Victor, Awadallah, Ahmed, Kamar, Ece, Hosn, Rafah, Amershi, Saleema
Modern AI agents, driven by advances in large foundation models, promise to enhance our productivity and transform our lives by augmenting our knowledge and capabilities. To achieve this vision, AI agents must effectively plan, perform multi-step rea
Externí odkaz:
http://arxiv.org/abs/2411.04468