Sensor systems typically operate under resource constraints that prevent the simultaneous
use of all resources all of the time. Sensor management becomes relevant when the sensing …

Foundations and Applications of Sensor Management presents the emerging theory of
sensor management with applications to real-world examples such as landmine detection …

Multi-armed bandit (MAB) problems are a class of sequential resource allocation problems
concerned with allocating one or more resources among several alternative (competing) …

Where should we place sensors to efficiently monitor natural drinking water resources for
contamination? Which blogs should we read to learn about the biggest stories on the Web …

A methodology is developed for planning the sensing strategy of a robotic sensor deployed
for the purpose of classifying multiple fixed targets located in an obstacle-populated …

We study reinforcement learning with function approximation for large-scale Partially
Observable Markov Decision Processes (POMDPs) where the state space and observation …

Adaptive sensing involves actively managing sensor resources to achieve a sensing task,
such as object detection, classification, and tracking, and represents a promising direction …

Partially observable Markov decision processes (POMDPs) provide a principled framework
for modeling an agent's decision-making problem when the agent needs to consider noisy …

Many real-world decision making tasks require us to choose among several expensive
observations. In a sensor network, for example, it is important to select the subset of sensors …

Many practical applications, such as environmental monitoring or placing sensors for event
detection, require to select among a set of informative but possibly expensive observations …