Recently, a convergence proof of stochastic search algorithms toward finite size Pareto set approximations of continuous multi-objective optimization problems has been given. The...
In this paper, we describe the partially observable Markov decision process pomdp approach to nding optimal or near-optimal control strategies for partially observable stochastic ...
Anthony R. Cassandra, Leslie Pack Kaelbling, Micha...
This work describes a stochastic approach for the optimal placement of sensors in municipal water networks to detect maliciously injected contaminants. The model minimizes the exp...
The sensor scheduling problem can be formulated as a controlled hidden Markov model and this paper solves the problem when the state, observation and action spaces are continuous....
Sumeetpal S. Singh, Nikolaos Kantas, Ba-Ngu Vo, Ar...
In this work, the authors have evaluated almost 20 millions ensembles of classifiers generated by several methods. Trying to optimize those ensembles based on the nearest neighbou...
Guillaume Tremblay, Robert Sabourin, Patrick Maupi...