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      저자 : Aloukik Aditya (검색결과 1 건)
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        Experiment in Using Reinforcement Learning in Gaming: The Breakout Game Learning

        Taresh Dewan,Aloukik Aditya,Manva Trivedi,Ao Chen,Danning Jiang,Sabah Mohammed 한국컴퓨터게임학회 2021 한국컴퓨터게임학회논문지 Vol.34 No.2

        In this study, we investigated whether a tool such as a game toy can be used as an augmented reality tool, and a system model that can be extended to a game element using wireless communication technology such as Bluetooth and a controllable module. This is an online ship type game using augmented reality technology and wireless communication technology. In addition, the existing game element was extended by applying a smartphone app control module. The existing game method uses the method of playing the game with only limited functions in the same space. This study expands to augmented reality-based games by implementing contents in a way that matches game objects with the grafting of augmented reality technology, and uses various items that emerge as the limit of reality. Therefore, we standardized the size of game objects so that they can be used three-dimension in all spaces on the screen according to the space arrangement such as overlapping prevention, distance, and height, and augmented reality technology was used to allow the game to be played by manipulation of a smartphone. In addition, we propose a system framework-based model that can be applied to various games, and a framework that can implement various augmented reality environments. The augmented reality-based battle game proposed in this study combines a knowledge-based augmented reality system that can be extended to game elements by modularizing the function of a toy through+ a context-aware agent based on context information and an intelligent DB based on domain knowledge.

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