Buch, Englisch, 200 Seiten, Format (B × H): 155 mm x 235 mm
China Conference, CCLD 2025, Suzhou, China, December 4–6, 2025, Revised Selected Papers
Buch, Englisch, 200 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Communications in Computer and Information Science
ISBN: 978-981-9255-10-8
Verlag: Springer
This book constitutes the refereed post proceedings of the China Conference on Large Foundation Model and Decision Intelligence, CCLD 2025, held in Suzhou, China, during December 4–6, 2025.
The 14 full papers included in this book were carefully reviewed and selected from 51 submissions. They cover a broad spectrum of cutting-edge topics, including Large Models and Complex Systems, Intelligent Command & Control, World Models and Spatial Intelligence, Human-Machine Mixed Decision Making, Embodied Intelligence, Generative Art, Scientific Intelligence, Intelligent Game Decision Making, Algorithmic Competition, Safety Alignment, and Brain-like Intelligence.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
Weitere Infos & Material
.- Foundations and Algorithms of Large Language Models .
.- Differential Private Federated Learning with Gradient-Aware Dynamic Personalization.
.- Semantic-Attention Decoupling for Enhanced Controllability in Diffusion Models.
.- Anchor-based Selective Unlearning for Case-level Forgetting in Domain-specific LLMs.
.- Attention Mechanism in Large-Model Architectures: A Survey.
.- Intelligent Decision-Making and Multi-Agent Systems .
.- Multi-UAV Collaborative Decision-Making Control Method Based on Deep Reinforcement Learning.
.- A LLM-powered dynamic incentive collaborative MARL framework.
.- Research on Air Target Combat Intention Prediction Based on TSAFNet-GA.
.- A Countermeasure Strategy Generation Method Based on Task Focus Drift Analysis.
.- Simulation Deduction and Evaluation with Multi-Agent Collaboration.
.- Embodied-AI with Large Models Research and Challenges.
.- EnerAgentic:Multi-Agent Large Language Models for Assisting Scientific Research Tasks in Integrated Energy Systems.
.- DECIS: LLM-Based Value Assessment Framework for Targets.
.- A Multi-Agent Collaborative Optimization Framework for Integrated Energy System Scheduling.
.- Flexible Multi-Timescale Optimization of Heterogeneous Equipment in Electro-Thermal-Hydrogen Energy Supply Systems for Chemical Industrial Parks.
