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Multiagent Patrol Generalized to Complex Environmental Conditions.
Noa Agmon,
Daniel Urieli, and Peter Stone.
In
Proceedings of the Twenty-Fifth Conference on ArtificialIntelligence (AAAI), August 2011.
Extended
version, book
chapter
[PDF]323.8kB [postscript]1.9MB
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.
@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.
},
wwwnote={<a href="http://www.cs.utexas.edu/~pstone/Papers/2011aaai/AAAI11-agmon-extended.pdf">Extended version</a>, <a href="https://www.morebooks.de/store/gb/book/advanced-in-marine-robotics/isbn/978-3-659-41689-7">book</a> chapter},
}
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