Learning cooperative object pushing with variable contact point

Learning in multi-agent environments where each agent's action directly affects other agents would be an important matter and a complicated task. To reduce the learning time and simplifying the learning process, it is suitable to learn individual skills and then provide cooperation and coordination utilizing the learned individual skills. In the approach proposed in this paper, agents benefit from their individual knowledge obtained in the individual learning phase to cooperate with other agents. Cooperative object pushing system is used as a testbed to our proposed method where cooperation and coordination between agents are needed in these systems. Agents independently learn to push the object to the target by using the proposed fuzzy reinforcement learning method. Agents attain their cooperative behaviors properly making use of the coded knowledge in the Q-table. Simulation and experimental results show that by interpreting the knowledge in the Q-table, agents can achieve high level behaviors with a high degree of cooperation.