Using Collective Intelligence to Route Internet Traffic

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 thattheory to design COINs to control internet traffic routing. These experiments indicate that COINs outperform all previously investigated RL-based, shortest path routing algorithms. 1 INTRODUCTION COllective INtelligences (COINs) are large, sparsely connected recurrent neural networks, whose "neurons" are reinforcement learning (RL) algorithms. The distinguishing featureof COINs is that their dynamics involves no centralized control, but only the collective effects of the individual neurons each modifying their behavior viatheir individual RL algorithms. This restriction holds even though the goal of the COIN concerns the system's global behavior.