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@InProceedings{AAAI11-agmon,
  author = {Noa Agmon and Daniel Urieli and Peter Stone},
  title = {Multiagent Patrol Generalized to Complex Environmental Conditions},
  booktitle="Proceedings of the Twenty-Fifth Conference on Artificial
Intelligence (AAAI)",
  month="August",
  year="2011", 
  abstract = {
    The problem of multiagent patrol has gained considerable attention
    during the past decade, with the immediate applicability of the
    problem being one of its main sources of interest. In this paper
    we concentrate on frequency-based patrol, in which the agents'
    goal is to optimize a frequency criterion, namely, minimizing the
    time between visits to a set of interest points. We consider
    multiagent patrol in environments with complex environmental
    conditions that affect the cost of traveling from one point to
    another. For example, in marine environments, the travel time of
    ships depends on parameters such as wind, water currents, and
    waves. We demonstrate that in such environments there is a need to
    consider a new multiagent patrol strategy which divides the given
    area into parts in which more than one agent is active, for
    improving frequency. We show that in general graphs this problem
    is intractable, therefore we focus on simplified (yet realistic)
    cyclic graphs with possible inner edges.
    Although the problem remains generally intractable in such graphs,
    we provide a heuristic algorithm that is shown to significantly
    improve point-visit frequency compared to other patrol
    strategies. For evaluation of our work we used a custom developed
    ship simulator that realistically models ship movement constraints
    such as engine force and drag and reaction of the ship to
    environmental changes.
  },
}