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Disambiguation Protocols Based on Risk Simulation
Fishkind, D.E.
Priebe, C.E.
Giles, K.E.
Smith, L.N.
Aksakalli, V.
Johns Hopkins Univ., Baltimore;
This paper appears in: Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
Publication Date: Sept. 2007
Volume: 37,
Issue: 5
On page(s): 814-823
ISSN: 1083-4427
INSPEC Accession Number: 9610138
Digital Object Identifier: 10.1109/TSMCA.2007.902634
Current Version Published: 2007-08-20
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Suppose there is a need to swiftly navigate through a spatial arrangement of possibly forbidden regions, with each region marked with the probability that it is, indeed, forbidden. In close proximity to any of these regions, you have the dynamic capability of disambiguating the region and learning for certain whether or not the region is forbidden - only in the latter case may you proceed through that region. The central issue is how to most effectively exploit this disambiguation capability to minimize the expected length of the traversal. Regions are never entered while they are possibly forbidden, and thus, no risk is ever actually incurred. Nonetheless, for the sole purpose of deciding where to disambiguate, it may be advantageous to simulate risk, temporarily pretending that possibly forbidden regions are riskily traversable, and each potential traversal is weighted with its level of undesirability, which is a function of its traversal length and traversal risk. In this paper, the simulated risk disambiguation protocol is introduced, which has you follow along a shortest traversal - in this undesirability sense - until an ambiguous region is about to be entered; at that location, a disambiguation is performed on this ambiguous region. (The process is then repeated from the current location, until the destination is reached.) We introduce the tangent arc graph as a means of simplifying the implementation of simulated risk disambiguation protocols, and we show how to efficiently implement the simulated risk disambiguation protocols that are based on linear undesirability functions. The effectiveness of these disambiguation protocols is illustrated with examples, including an example that involves mine countermeasures path planning.
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