63 citations · 91 across the 8 of their papers we have counts for
5 papers · 1 filter
Avoiding Braess' Paradox through Collective Intelligence
Kagan Tumer, David H. Wolpert
In an Ideal Shortest Path Algorithm (ISPA), at each moment each router in a network sends all of its traffic down the path that will incur the lowest cost to that traffic. In the l…
Adaptivity in Agent-Based Routing for Data Networks
David H. Wolpert, Sergey Kirshner, Chris J. Merz +1
Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems (MAS's) in noisy environments. O…
An Introduction to Collective Intelligence
David H. Wolpert, Kagan Tumer
This paper surveys the emerging science of how to design a ``COllective INtelligence'' (COIN). A COIN is a large multi-agent system where: (i) There is little to no centralized com…
General Principles of Learning-Based Multi-Agent Systems
David H. Wolpert, Kevin R. Wheeler, Kagan Tumer
We consider the problem of how to design large decentralized multi-agent systems (MAS's) in an automated fashion, with little or no hand-tuning. Our approach has each agent run a r…
Using Collective Intelligence to Route Internet Traffic
David H. Wolpert, Kagan Tumer, Jeremy Frank
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 globa…