Integrating the various embedded devices and systems in our environment enables an
Internet of Things (IoT) for a smart city. The IoT will generate tremendous amount of data that …

Within the context of multiple mobile, and networked robot systems, this chapter explores the
current state of the art. After a brief introduction, we first examine architectures for multirobot …

The deployment problem (DP) of a wireless sensor network (WSN) is no doubt a critical
issue because the strategies it takes will not only strongly impact the overall performance but …

Submodularity1 is a property of set functions with deep theoretical consequences and far–
reaching applications. At first glance it appears very similar to concavity, in other ways it …

Information theoretic active learning has been widely studied for probabilistic models. For
simple regression an optimal myopic policy is easily tractable. However, for other tasks and …

Robotic systems are increasingly being utilized as fundamental data-gathering tools by
scientists, allowing new perspectives and a greater understanding of the planet and its …

When monitoring spatial phenomena, which can often be modeled as Gaussian processes
(GPs), choosing sensor locations is a fundamental task. There are several common …

Recently active learning has attracted a lot of attention in computer vision field, as it is time
and cost consuming to prepare a good set of labeled images for vision data analysis. Most …

There has been much progress recently on improved approximations for problems involving
submodular objective functions, and many interesting techniques have been developed …

We investigate two new optimization problems—minimizing a submodular function subject
to a submodular lower bound constraint (submodular cover) and maximizing a submodular …