Market-based control: a paradigm for distributed resource allocation
Market-based control: a paradigm for distributed resource allocation
InfoSleuth: agent-based semantic integration of information in open and dynamic environments
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Market-based resource control for mobile agents
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Price-war dynamics in a free-market economy of software agents
ALIFE Proceedings of the sixth international conference on Artificial life
Comparative Models of the File Assignment Problem
ACM Computing Surveys (CSUR)
Modelling Market-Based Decentralised Management Systems
BT Technology Journal
The WALRAS Algorithm: A Convergent Distributed Implementation of General Equilibrium Outcomes
Computational Economics
Market-Based Call Routing in Telecommunications Networks Using Adaptive Pricing and Real Bidding
IATA '99 Proceedings of the Third International Workshop on Intelligent Agents for Telecommunication Applications
Some Economics of Market-Based Distributed Scheduling
ICDCS '98 Proceedings of the The 18th International Conference on Distributed Computing Systems
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Multi-agent based global information systems present one of the broadest and most compelling areas for market-based control. Their inherently distributed and heterogeneous nature combined with their vast size makes traditional centralized control methods impractical. We use the 'invisible hand' of markets to guide agent decisions without centralized management. While most market-based studies impose auction mechanisms to drive market convergence, in our system the continual adaptation of the 'information economy' is ab emergent effect, fuelled by competition between autonomous self-interested agents acting on locally gathered information. We argue that due to market-based competition an environment tailored to consumer requirements will emerge. We focus on agents competing using mobility to adapt their location in response to consumer demand. In this modern version of the data allocation problem, we demonstrate that even simple decentralized mobility strategies can produce agent allocations comparable to centralized heuristic algorithms. Furthermore, we demonstrate that where agents implement competing strategies, due to market-based competition the agents that best satisfy consumer requirments will populate the emergent environment.