惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

博客园_首页
Y
Y Combinator Blog
Engineering at Meta
Engineering at Meta
D
Docker
GbyAI
GbyAI
aimingoo的专栏
aimingoo的专栏
大猫的无限游戏
大猫的无限游戏
腾讯CDC
P
Proofpoint News Feed
A
About on SuperTechFans
WordPress大学
WordPress大学
Stack Overflow Blog
Stack Overflow Blog
Google DeepMind News
Google DeepMind News
C
Check Point Blog
Microsoft Security Blog
Microsoft Security Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
L
LangChain Blog
MyScale Blog
MyScale Blog
博客园 - 三生石上(FineUI控件)
Hugging Face - Blog
Hugging Face - Blog
Microsoft Azure Blog
Microsoft Azure Blog
N
Netflix TechBlog - Medium
G
Google Developers Blog
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻

cs.SI updates on arXiv.org

Hiding in Plain Sight: Finding MAHA on Reddit Prism: Structural Symmetry Scanning via Duality-Constrained Laplacian Projection MV-Gate: Insider Threat Detection via Multi-View Behavioral Statistics and Semantic Modeling Algorithmic Cultivation: How Social Media Feeds Shape User Language Universal Dynamics of Punctuated Progress AI-Mediated Communication Can Steer Collective Opinion CitePrism: Human-in-the-Loop AI for Citation Auditing and Editorial Integrity Explainable Detection of Depression Status Shifts from User Digital Traces Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles Humanwashing -- It Should Leave You Feeling Dirty When Do LLMs Generate Realistic Social Networks? A Multi-Dimensional Study of Culture, Language, Scale, and Method Moltbook Moderation: Uncovering Hidden Intent Through Multi-Turn Dialogue Linking Extreme Discourse to Structural Polarization in Signed Interaction Networks Predicting Channel Closures in the Lightning Network with Machine Learning Latent Causal Void: Explicit Missing-Context Reconstruction for Misinformation Detection Predictive Maps of Multi-Agent Reasoning: A Successor-Representation Spectrum for LLM Communication Topologies Large Language Models for Causal Relations Extraction in Social Media: A Validation Framework for Disaster Intelligence When Can Digital Personas Reliably Approximate Human Survey Findings? RAwR: Role-Aware Rewiring via Approximate Equitable Partition GravityGraphSAGE: Link Prediction in Directed Attributed Graphs Structure-Centric Graph Foundation Model via Geometric Bases Attention-based graph neural networks: a survey When AI Meets Science: Research Diversity, Interdisciplinarity, Visibility, and Retractions across Disciplines in a Global Surge Scalable inference of spatial regions and temporal signatures from time series Can LLMs Emulate Human Belief Dynamics? Predicting Post Virality with Temporal Cross-Attention over Trend Signals H3: A Healthcare Three-Hop Index for Physician Referral Network Prediction Dynamic Graph with Similarity-Aware Attention Graph Neural Network for Recommender Systems Spectral Graph Sparsification Preserves Representation Geometry in Graph Neural Networks
On the Convergence of the Hegselmann-Krause System
Arnab Bhattacharyya, Mark Braverman, Bernard Chazelle, Huy L. Ng · 2012-11-09 · via cs.SI updates on arXiv.org

We study convergence of the following discrete-time non-linear dynamical system: n agents are located in R^d and at every time step, each moves synchronously to the average location of all agents within a unit distance of it. This popularly studied system was introduced by Krause to model the dynamics of opinion formation and is often referred to as the Hegselmann-Krause model. We prove the first polynomial time bound for the convergence of this system in arbitrary dimensions. This improves on the bound of n^{O(n)} resulting from a more general theorem of Chazelle. Also, we show a quadratic lower bound and improve the upper bound for one-dimensional systems to O(n^3).