I'm on a research of problem, when there is $N$ agents, that work together as a team. Let's assume that they try to destroy as much targets as possible while having limited ammunition. There is also $M$ targets with unknown positions.
Any of agents has limited visibility range. Any member of the team can locate target, when latter got in a visibility range. When agent locates the target, he can take one of two actions: attack or continue searching.
The main point is to make target assignment in a way, that no target would be attacked by more than one agent (I'm not sure if it must be strict requirement). I think, that target selection must be based on some payoffs, for example: probability of destroying target, probability of successful search of new targets, etc.
For simplicity, I assume, that this problem is solved as static: we models some situation, when each team member stands in certain position and observers some targets.
I think that it's an optimization problem, where agents not only maximize their own payoff-functions, but also global (or team) payoff.
Also, one important restriction must be total absence of communication between agents. Consequently, any agent has information only about positions of other team members and targets that fall into his own visibility zone.
My intuition suggests me, that this problem falls into game theoretical field. Because any agent must "play" with his neighbors to decide, who must attack concrete target. As for restriction on communication, it might be game with imperfect information, but my knowledge in this field is very little. I started studying game theory not so long ago.
For today, I found an article on this topic. It's very similar to my research, but, if I understood it correctly, they assume communication during negotiation rounds.
I would be very happy, if anybody points me at concrete literature, researches or topics on this problem. Any suggestions on a problem formulation are welcome.