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  1. Abstract This work presents a deep reinforcement learning (DRL) approach for procedural content generation (PCG) to automatically generate three-dimensional (3D) virtual environments that users can interact with. The primary objective of PCG methods is to algorithmically generate new content in order to improve user experience. Researchers have started exploring the use of machine learning (ML) methods to generate content. However, these approaches frequently implement supervised ML algorithms that require initial datasets to train their generative models. In contrast, RL algorithms do not require training data to be collected a priori since they take advantage of simulation to train their models. Considering the advantages of RL algorithms, this work presents a method that generates new 3D virtual environments by training an RL agent using a 3D simulation platform. This work extends the authors’ previous work and presents the results of a case study that supports the capability of the proposed method to generate new 3D virtual environments. The ability to automatically generate new content has the potential to maintain users’ engagement in a wide variety of applications such as virtual reality applications for education and training, and engineering conceptual design. 
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  2. With design teams becoming more distributed, the sharing and interpreting of complex data about design concepts/prototypes and environments have become increasingly challenging. The size and quality of data that can be captured and shared directly affects the ability of receivers of that data to collaborate and provide meaningful feedback. To mitigate these challenges, the authors of this work propose the real-time translation of physical objects into an immersive virtual reality environment using readily available red, green, blue, and depth (RGB-D) sensing systems and standard networking connections. The emergence of commercial, off-the-shelf RGB-D sensing systems, such as the Microsoft Kinect, has enabled the rapid three-dimensional (3D) reconstruction of physical environments. The authors present a method that employs 3D mesh reconstruction algorithms and real-time rendering techniques to capture physical objects in the real world and represent their 3D reconstruction in an immersive virtual reality environment with which the user can then interact. Providing these features allows distributed design teams to share and interpret complex 3D data in a natural manner. The method reduces the processing requirements of the data capture system while enabling it to be portable. The method also provides an immersive environment in which designers can view and interpret the data remotely. A case study involving a commodity RGB-D sensor and multiple computers connected through standard TCP internet connections is presented to demonstrate the viability of the proposed method. 
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