This thesis contributes to the understanding of the intentional cooperation in multi-robot systems. We show that in a complex multi-robot system cooperation is achieved implicitly through the mediation of the independent decisions of the individual agents that are made autonomously. We assert that in order for a multi-robot system to accomplish a mission cooperatively, it is necessary for the individuals to proactively contribute to planning, to incremental refinement, as well as to adaptation at the group-level as the state of the mission progresses. We show how the decomposition of a mission delegated to a multi-robot system provides the agents with the ability to make decisions in a distributed fashion. While formulating decision mechanism, we show how the state of a robotic agent with respect to the delegated mission is viewed as two independent internal and external states. Furthermore, we demonstrate the requirement of a priori knowledge in decision process is prevented via incorporation of a simple sub-ranking module into the external state component of the decision mechanism of the robotic agents. While this independent involvement of the robotic agents in decision-making process preserves the autonomy of the individual agents, we show the mediation of these independent decisions does not only ensure proper execution of the plan but serves as a basis for the evolution of the intentional cooperation among the robotic agents.