Simulation games can be a catalyst for understanding manufacturing systems concepts among engineering students. Integrating manufacturing simulations with virtual reality (VR) allows students to visualize, manipulate and interact with computers and extremely complex data. This paper discusses the use of simulation to teach manufacturing concepts. We developed five physical simulation games for the different manufacturing environments (i.e., craft production, mass production, lean production, mass customization, and personalized production). We then developed corresponding digital simulations and integrated them with virtual reality technology. This paper focuses on the development of a virtual reality simulation for craft production. Manufacturing concepts such as inventory planning, production scheduling, and process improvement (Lean and Six Sigma methodologies) will also be considered. By comparing physical simulations with virtual reality environments, this paper provides insights into the applicability of virtual reality technologies in the education domain. Research activities will be integrated into undergraduate courses on manufacturing systems to support problem-solving skill development among students.
Our goal is to provide learning mechanisms to game agents so they are capable of adapting to new behaviors based on the actions of other agents. We introduce a new on-line reinforcement learning (RL) algorithm, ALeRT-AM, that includes an agent-modeling mechanism. We implemented this algorithm in BioWare Corp.’s role-playing game, Neverwinter Nights to evaluate its effectiveness in a real game. Our experiments compare agents who use ALeRT-AM with agents that use the non-agent modeling ALeRT RL algorithm and two other non-RL algorithms. We show that an ALeRT-AM agent is able to rapidly learn a winning strategy against other agents in a combat scenario and to adapt to changes in the environment.
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