![]() ![]() However, it is not easy to make a robot behave like a human in dynamic environments. In general, robots are required to work effectively and safely in a dynamic environment to achieve their tasks. Various robots have been developed to assist humans in workspaces, such as a house or factory. Over the years, many studies have been conducted with the objective of facilitating the working of robots in dynamic environments. As a result, the proposed method has been confirmed that is provided suitable solution for an approach to the goal for the agents. From this viewpoint, in this study aims to improve maze-solving technique, efficiency by which to the multi-agent reinforcement learning's agents under the situation. In addition, sometimes the any information won't be transmitted in the situation of knowledge sharing. In this study, the proposed method has been using two type agents that communicate as information exchange on the location to settle this problem, moreover, the noise will be mixed with knowledge space in the situation of the knowledge sharing. In addition, a time per a episode will enlarge because an agent will be explored in a given area. Moreover, it is hard to learn the reinforcement learning agent in the actual environment cause of some noise of actual environment or source device. However, there is a limit on the information of the sensors. In reinforcement learning, this method will be supposed that agent is able to observe the environment, completely. ![]() In this study, the reinforcement learning agent under the situation of communicable as multi-agent system will be improved efficiency. ![]()
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