Abstract—In this article, a new hybrid feedback system is introduced, which integrates the behavior- based planning by reactive agent-based control scheme through subsumption architecture. At first, subsumption protocol studies the interactions of robot with its environment which cover problems including translating of agent action into an outcome, interactions with the environment, and cooperative actions. Second considers deliberative behavior given the prevailing protocol. It determines the best and quickest response for each agent and tunes the actions based on an objective function obtained by a leader agent. More specifically, tasks are arranged as a hierarchy, where the high-level task is obstacle avoidance. Conflicting lower level tasks are removed by the leader agent decisions. Indeed, the leader agent can adjust the priority of all action to provide an optimal behavior. In other words, our new agent-based method optimizes the subsumption architecture by producing an approximating objective function that made not only behaviors but also optimization done in incremental procedure. We also define an emergency avoidance factor that made higher speed still stable and better interaction of robot in the presence of obstacles. For obstacles avoidance, the leader agent projects a plane to investigate the space ahead and continues. Finally, the leader agent makes a basic stand by task sharing behaviors in decentralized manner using subsumption architecture to draw an optimal path. Simulation results show that although the proposed apporach has little knowledge about the unexpected and adhoc situation in the robot’s environment, it is able to provide suitable performance.