Autonomous agents are designed to reach goals that were pre-de ned by their operators. An important way to execute tasks and to maximize payo is to share resources and to cooperate on task execution by creating coalitions of agents. Such coalitions will take place if, and only if, each member of a coalition gains more if he joins the coalition than he could gain before. There are several ways to create such coalitions and to divide the joint payo among the members. Variance in these methods is due to di erent environments, di erent settings in a speci c environment, and di erent approaches to a speci c environment with speci c settings. In this paper we focus on the cooperative super-additive environment, and suggest two di erent algorithms for coalition formation and payo distribution in this environment. We also deal with the complexity of both computation and communication of each algorithm, and we try to give designers some basic tools for developing agents for this environment. ...