A path-planning algorithm to guide unmanned aerial vehicles (UAVs) for tracking multiple
ground targets based on the theory of partially observable Markov decision processes …

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 …

We address the problem of controlling a mobile robot to explore a partially known
environment. The robot's objective is the maximization of the amount of information collected …

A unique guide to the state of the art of tracking, classification, and sensor management This
book addresses the tremendous progress made over the last few decades in algorithm …

Real-time pricing (RTP) is a utility-offered dynamic pricing program to incentivize customers
to make changes in their energy usage. A home energy management system (HEMS) …

In traditional decision-theoretic planning, information gathering is a means to a goal. The
agent receives information about its environment (state or observation) and uses it as a way …

In this paper, we present a decentralized unmanned aerial vehicle (UAV) swarm formation
control approach based on a decision theoretic approach. Specifically, we pose the UAV …

Cognitive radar is a radar system that acquires knowledge and understanding of its
operating environment through online estimation, reasoning and learning or from databases …

Previous works have identified key characteristics of a cognitive radar, such as knowledge
exploitation, perception, action, memory, intelligence and attention. In this work, it is argued …

We consider an inverse reinforcement learning problem involving “us” versus an “enemy”
radar equipped with a Bayesian tracker. By observing the emissions of the enemy radar …