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Issue No.01 - January/February (2009 vol.24)
pp: 18-21
Kagan Tumer , Oregon State University
Adrian Agogino , University of California, Santa Cruz
Air traffic management is a fundamental challenge facing the US Federal Aviation Administration (FAA) and, owing to the difficulties in improving the infrastructure, a problem in need of an algorithmic solution. A proposed multiagent approach assigns an agent to a navigational fix (a specific location in 2D space) and derives specific agent rewards that shape the agent actions. These agents aim to maximize their own local rewards, but their doing so leads to coordinated behavior that reduces global congestion.
multiagent coordination, multiagent learning, air traffic management
Kagan Tumer, Adrian Agogino, "Improving Air Traffic Management with a Learning Multiagent System", IEEE Intelligent Systems, vol.24, no. 1, pp. 18-21, January/February 2009, doi:10.1109/MIS.2009.10
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7. K. Tumer and A. Agogino, "Distributed Agent-Based Air Traffic Flow Management," Proc. 6th Int'l Joint Conf. Autonomous Agents and Multiagent Systems (AAMAS 07), Int'l Foundation for Autonomous Agents and Multiagent Systems, 2007, pp. 330–337.
8. K. Tumer, "Designing Agent Utilities for Coordinated, Scalable and Robust Multi-agent Systems," Challenges in the Coordination of Large Scale Multiagent Systems, P. Scerri, R. Mailler, and R. Vincent eds., Springer, 2005, pp. 173–188.
9. K. Tumer, and D. Wolpert, "A Survey of Collectives," Collectives and the Design of Complex Systems, Springer, 2004, pp. 1–42.
10. A.K. Agogino and K. Tumer, "Handling Communication Restrictions and Team Formation in Congestion Games," J. Autonomous Agents and Multi-agent Systems, vol. 13, no. 1, 2006, pp. 97–115.
11. D.H. Wolpert and K. Tumer, "Collective Intelligence, Data Routing and Braess' Paradox," J. Artificial Intelligence Research, vol. 16, 2002, pp. 359–387.
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