  Humans can selectively focus on different information based on different
tasks requirements, other people's abilities and availability. Therefore, they
can adapt quickly to a completely different and complex environments. If, like
people, robot could obtain the same abilities, then it would greatly increase
their adaptability to new and unexpected situations. Recent efforts in
Heterogeneous Multi Robots Teaming have try to achieve this ability, such as
the methods based on communication and multi-modal information fusion
strategies. However, these methods will not only suffer from the exponential
explosion problem with the increase of robots number but also need huge
computational resources. To that end, we introduce an inner attention
actor-critic method that replicates aspects of human flexibly cooperation. By
bringing attention mechanism on computer vision, natural language process into
the realm of multi-robot cooperation, our attention method is able to
dynamically select which robots to attend to. In order to test the
effectiveness of our proposed method, several simulation experiments have been
designed. And the results show that inner attention mechanism can enable
flexible cooperation and lower resources consuming in rescuing tasks.
