The emergence of cooperation in a society of autonomous agents is investigated. Each agent is made to repetitively engage in a deal equivalent to the "Prisoner’s Dilemma" game, each time changing the other party of the deal. The conditions of the deal are that the contract histories of all the agents are disclosed to the public. Several deal strategies are evaluated, and their behaviors are investigated by matching them under various conditions. Next the social evolution of deal strategies is investigated using genetic algorithm techniques. Each agent can bear a child according to the profit he gets through the deal. The child inherits the deal strategy of the parent, but the random mutation is introduced to the inheritance of strategies. It is shown that the robust and cooperative strategies emerges through the evolution starting from a simple "Tit for Tat" algorithm.