Using Collective Intelligence to Route Internet Traffic
Machine Learning
2007-05-23 v1 adap-org
Statistical Mechanics
Distributed, Parallel, and Cluster Computing
Networking and Internet Architecture
Adaptation and Self-Organizing Systems
Abstract
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.
Cite
@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}
}
Comments
7 pages