Using Collective Intelligence to Route Internet Traffic

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dc.creatorWolpert, David H.
dc.creatorTumer, Kagan
dc.creatorFrank, Jeremy
dc.date1999-05-10
dc.date.accessioned2026-07-07T03:24:06Z
dc.date.available2026-07-07T03:24:06Z
dc.descriptionA 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.
dc.description7 pages
dc.identifierhttps://arxiv.org/abs/cs/9905004
dc.identifierhttp://arxiv.org/abs/cs/9905004
dc.identifierAdvances in Information Processing Systems - 11, eds M. Kearns, S. Solla, D. Cohn, MIT Press, 1999
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/33195
dc.subjectMachine Learning
dc.subjectAdaptation and Self-Organizing Systems
dc.subjectStatistical Mechanics
dc.subjectDistributed, Parallel, and Cluster Computing
dc.subjectNetworking and Internet Architecture
dc.subjectI.2.6; I.2.11
dc.titleUsing Collective Intelligence to Route Internet Traffic
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