Resource Allocation in Decentralised Computational Systems: An Evolutionary Market-Based Approach

Peter R. Lewis, Paul Marrow and Xin Yao
In Autonomous Agents and Multi-Agent Systems 21(2):143-171, 2010
(Runner-up in the BT Gordon Radley Award for "Best Author of Innovation" 2010.)

We present a novel market-based method, inspired by retail markets, for resource allocation in fully decentralised systems where agents are self-interested. Our market mechanism requires no coordinating node or complex negotiation. The stability of outcome allocations, those at equilibrium, is analysed and compared for three buyer behaviour models.

In order to capture the interaction between self-interested agents, we propose the use of
competitive coevolution. Our approach is both highly scalable and may be tuned to achieve specified outcome resource allocations. We demonstrate the behaviour of our approach in simulation, where evolutionary market agents act on behalf of service providing nodes to adaptively price their resources over time, in response to market conditions. We show that this leads the system to the predicted outcome resource allocation. Furthermore, the system remains stable in the presence of small changes in price, when buyers’ decision functions degrade gracefully.

@Article{ lewis_et_al_2010,
author = "Peter R. Lewis and Paul Marrow and Xin Yao",
title = "Resource Allocation in Decentralised Computational Systems: An Evolutionary Market Based Approach",
journal = "Autonomous Agents and Multi-Agent Systems",
year = "2010",
pages = "143--171",
volume = "21",
number = "2"
publisher = "Springer"
}