Ashley Llorens

REDD-RA1

Publications

We propose an ensemble approach for multi-target binary classification, where the target class breaks down into a disparate set of pre-defined target-types. The system goal is to maximize the probability of alerting on targets from any type while excluding background clutter. The agent-classifiers that make up the ensemble are binary classifiers tr   ...more

This paper provides a complexity analysis for the game of reconnaissance blind chess (RBC), a recently-introduced variant of chess where each player does not know the positions of the opponent's pieces a priori but may reveal a subset of them through chosen, private sensing actions. In contrast to many commonly studied imperfect information gam   ...more

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Ashley Llorens
Ashley.Llorens@jhuapl.edu
240-228-0312

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Laurel, MD 20723


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