Market-oriented programming: some early lessons
Market-based control
Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Multiagent systems: a modern approach to distributed artificial intelligence
Multiagent systems: a modern approach to distributed artificial intelligence
Dynamic pricing by software agents
Computer Networks: The International Journal of Computer and Telecommunications Networking - electronic commerce
Agents and The Internet: Infrastructure for Mass Customization
IEEE Internet Computing
The Dynamics of the UMDL Service Market Society
CIA '98 Proceedings of the Second International Workshop on Cooperative Information Agents II, Learning, Mobility and Electronic Commerce for Information Discovery on the Internet
Multiagent task allocation in social networks
Autonomous Agents and Multi-Agent Systems
On-line coordination: Event interaction and state communication between cooperative agents
Web Intelligence and Agent Systems
Robust distributed scheduling via time-period aggregation
Web Intelligence and Agent Systems
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We present a method for solving service allocation problems in which a set of services must be allocated to a set of agents so as to maximize a global utility. The method is completely distributed so it can scale to any number of services without degradation. We first formalize the service allocation problem and then present a simple hill-climbing, a global hill-climbing, and a bidding-protocol algorithm for solving it. We analyze the expected performance of these algorithms as a function of various problem parameters such as the branching factor and the number of agents. Finally, we use the sensor allocation problem, an instance of a service allocation problem, to show the bidding protocol at work. The simulations also show that phase transition on the expected quality of the solution exists as the amount of communication between agents increases.