  A team of robots sharing a common goal can benefit from coordination of the
activities of team members, helping the team to reach the goal more reliably or
quickly. We address the problem of coordinating the actions of a team of robots
with periodic communication capability executing an information gathering task.
We cast the problem as a multi-agent optimal decision-making problem with an
information theoretic objective function. We show that appropriate techniques
for solving decentralized partially observable Markov decision processes
(Dec-POMDPs) are applicable in such information gathering problems. We quantify
the usefulness of coordinated information gathering through simulation studies,
and demonstrate the feasibility of the method in a real-world target tracking
domain.
