Market-based control: a paradigm for distributed resource allocation
Market-based control: a paradigm for distributed resource allocation
Gossip-based aggregation in large dynamic networks
ACM Transactions on Computer Systems (TOCS)
Computational-Mechanism Design: A Call to Arms
IEEE Intelligent Systems
Tycoon: An implementation of a distributed, market-based resource allocation system
Multiagent and Grid Systems
Distributed agent-based air traffic flow management
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Evaluating the performance of DCOP algorithms in a real world, dynamic problem
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
A multiagent approach to autonomous intersection management
Journal of Artificial Intelligence Research
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The control of large-scale open distributed systems, where many autonomous, intelligent entities interact with the environment and with each other, is not a trivial task. Market-based methods have been applied to the design and the control of such systems, by defining the "rules of the game" in such a way that a desired global outcome is obtained without any centralized decision making. The future traffic control systems, where intelligent infrastructures with sensors and computing power will interact with millions of drivers commuting from their homes to their respective workplaces, are an example of such systems. In this paper we model the traffic as a computational economy, where drivers trade with the intelligent infrastructure in a virtual marketplace. We design market rules to align the "global profit" (revenues from the infrastructure use) with the "social welfare" (average travel time), in a way that, in situations of similar traffic load, an increase of the infrastructure's monetary benefit usually implies a decrease of the drivers' average travel time.