CAMEG - A multi-agent based context-aware mobile educational game for on-the-job training

In this paper, we present a multi-agent based context-aware mobile educational game that can generate a series of learning activities for users doing on-the-job training in their working environment. We apply multi-agent architecture (MAA) into the mobile educational game design to achieve the goals of developing a lightweight, flexible, and scalable game on the platform with limited resources such as mobile phones. Multi-agent architecture not only makes different agents have its own tasks, but also provides developers an expandable way to add further functions into the game and to polish agents in order to make improvement on the game. This research focuses on designing the tasks that each agent needs to do and the communications may happen among agents. The benefits of the proposed multi-agent architecture game design makes the game itself easy to maintain and to expand, at meanwhile, reduces computing power consumed by the systems due to not all agents will be needed at same time.