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Sensor platforms with active sensing equipment such as radars may betray their existence, by emitting energy that can be intercepted by enemy surveillance sensors thereby increasing the vulnerability of the whole combat system. To achieve the important tactical requirement of low probability of intercept (LPI) requires dynamically controlling the emission of platforms. In this paper we propose computationally efficient dynamic emission control and management algorithms for multiple networked heterogenous platforms. By formulating the problem as a partially observed Markov decision process (POMDP) with an on-going multi-armed bandit structure, near optimal sensor management algorithms are developed for controlling the active sensor emission to minimize the threat posed to all the platforms. Numerical examples are presented to illustrate these control/management algorithms.