The problem of multi-agent robotic survey of an unknown area is approached through a game theoretic frame-work. This is meant to enable cooperation in the group of robotic explorers reflecting their common objectives to minimize the effort in the surveying task, without requiring expensive exchanges of signaling. The game theoretic approach can be applied to avoid any preliminary planning, but just exploiting the ability of the robots to take smart actions based on the state of the environment and the behaviors of other neighboring agents. We discuss how the choice of different utility functions can improve the collaboration among the robots and lead to more efficient results.
