Using Collective Intelligence to Route Internet Traffic
机器学习
2007-05-23 v1 adap-org
统计力学
分布式、并行与集群计算
网络与互联网体系结构
适应与自组织系统
摘要
A COllective INtelligence (COIN) is a set of interacting reinforcement learning (RL) algorithms designed in an automated fashion so that their collective behavior optimizes a global utility function. We summarize the theory of COINs, then present experiments using that theory to design COINs to control internet traffic routing. These experiments indicate that COINs outperform all previously investigated RL-based, shortest path routing algorithms.
引用
@article{arxiv.cs/9905004,
title = {Using Collective Intelligence to Route Internet Traffic},
author = {David H. Wolpert and Kagan Tumer and Jeremy Frank},
journal= {arXiv preprint arXiv:cs/9905004},
year = {2007}
}
备注
7 pages