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  • A Multiagent Approach to Managing Air Traffic Flow

    Creator:
    Agogino, Adrian K. and Tumer, Kagan
    Abstract:
    Intelligent air traffic flow management is one of the fundamental challenges facing the Federal Aviation Administration (FAA) today. FAA estimates put weather, routing decisions and airport condition induced delays at 1,682,700 h in 2007 (FAA OPSNET Data, US Department of Transportation website, http://www.faa.gov/data_statistics/), resulting in a staggering economic loss of...
    Resource Type:
    Article
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    10.1007/s10458-010-9142-5 A multiagent approach to managing air traffic flow Adrian K. Agogino · Kagan

  • Learning indirect actions in complex domains: action suggestions for air traffic control

    Creator:
    Agogino, Adrian and Tumer, Kagan
    Abstract:
    Providing intelligent algorithms to manage the ever-increasing flow of air traffic is critical to the efficiency and economic viability of air transportation systems. Yet, current automated solutions leave existing human controllers “out of the loop" rendering the potential solutions both technically dangerous (e.g., inability to react to suddenly developing conditions)...
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    Article
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    Suggestions for Air Traffic Control ∗ Adrian Agogino UCSC, NASA Ames Research Center, Mailstop 269-3 Moffett

  • Multirobot Coordination for Space Exploration

    Creator:
    Yliniemi, Logan, Agogino, Adrian K., and Tumer, Kagan
    Abstract:
    Teams of artificially intelligent planetary rovers have tremendous potential for space exploration, allowing for reduced cost, increased flexibility, and increased reliability. However, having these multiple autonomous devices acting simultaneously leads to a problem of coordination: to achieve the best results, they should work together. This is not a simple task....
    Resource Type:
    Article
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    Space Exploration Logan Yliniemi, Adrian K. Agogino, Kagan Turner • Teams of artificially

  • A Neuro-evolutionary Approach to Control Surface Segmentation for Micro Aerial Vehicles

    Creator:
    Salichon, Max and Tumer, Kagan
    Abstract:
    This paper addresses control surface segmentation in micro aerial vehicles (MAVs) by leveraging neuro-evolutionary techniques that allow the control of a higher number of control surfaces. Applying classical control methods to MAVs is a difficult process due to the complexity of the control laws with fast and highly non-linear dynamics....
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    Article
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    York, 2004. [31] Kagan Tumer and Adrian Agogino. Distributed evaluation functions for fault tolerant