> For the complete documentation index, see [llms.txt](https://library.xrguild.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://library.xrguild.org/current-peer-reviewed-immersive-technologies/the-combination-of-artificial-intelligence-and-extended-reality-a-systematic-review.md). # The Combination of Artificial Intelligence and Extended Reality: A Systematic Review Artificial intelligence (AI) and extended reality (XR) differ in their origin and primary objectives. ## Overview **Authors:** Dirk Reiners, Mohammad Reza Davahli, Waldemar Karwowsk, Carolina Cruz-Neira **Publication Date:** 7 September 2021 **Link:** [https://www.frontiersin.org/journals/virtual-reality/articles/10.3389/frvir.2021.721933/full]() **Keywords:** Artificial intelligence, extended reality, learning environment, autonomous cars, robotics **Type:** Peer-Reviewed Journals/White Papers ## Summary Artificial intelligence (AI) and extended reality (XR) differ in their origin and primary objectives. However, their combination is emerging as a powerful tool for addressing prominent AI and XR challenges and opportunities for cross-development. To investigate the AI-XR combination, we mapped and analyzed published articles through a multi-stage screening strategy. We identified the main applications of the AI-XR combination, including autonomous cars, robotics, military, medical training, cancer diagnosis, entertainment, and gaming applications, advanced visualization methods, smart homes, affective computing, and driver education and training. In addition, we found that the primary motivation for developing the AI-XR applications include 1) training AI, 2) conferring intelligence on XR, and 3) interpreting XR- generated data. Finally, our results highlight the advancements and future perspectives of the AI-XR combination. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://library.xrguild.org/current-peer-reviewed-immersive-technologies/the-combination-of-artificial-intelligence-and-extended-reality-a-systematic-review.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.