This work proposes a WebXR-based cross-platform conceptual architecture,
leveraging the A-Frame and Networked-Aframe frameworks, in order to facilitate
the development of an open, accessible, and interoperable metaverse. By
introducing the concept of spatial web app, this research contributes to the
discourse on the metaverse, offering an architecture that democratizes access
to virtual environments and extended reality through the web, and aligns with
Tim Berners-Lee's original vision of the World Wide Web as an open platform in
the digital realm.

该研究提出了一个基于 WebXR 的跨平台概念架构，利用 A-Frame 和 Networked-Aframe 框架，旨在促进开放、可访问和互操作的元宇宙的发展。通过引入空间 Web 应用的概念，该研究为元宇宙的讨论做出了贡献，提供了一个通过 Web 民主化访问虚拟环境和扩展现实的架构，与 Tim Berners-Lee 对数字领域开放平台的原始愿景一致。

WebXR, A-Frame 与 Networked-Aframe 作为开放元宇宙的基础：一个概念架构

WebXR, A-Frame and Networked-Aframe as a Basis for an Open Metaverse: A  Conceptual Architecture

Conceptual architecture involves a highly creative exploration of novel
ideas, often taken from other disciplines as architects consider radical new
forms, materials, textures and colors for buildings. While today's generative
AI systems can produce remarkable results, they lack the creativity
demonstrated for decades by evolutionary algorithms. SCAPE, our proposed tool,
combines evolutionary search with generative AI, enabling users to explore
creative and good quality designs inspired by their initial input through a
simple point and click interface. SCAPE injects randomness into generative AI,
and enables memory, making use of the built-in language skills of GPT-4 to vary
prompts via text-based mutation and crossover. We demonstrate that compared to
DALL-E 3, SCAPE enables a 67% improvement in image novelty, plus improvements
in quality and effectiveness of use; we show that in just 3 iterations SCAPE
has a 24% image novelty increase enabling effective exploration, plus
optimization of images by users. We use more than 20 independent architects to
assess SCAPE, who provide markedly positive feedback.

SCAPE 是一种将进化算法与生成性人工智能相结合的工具，通过简单的点选界面，使用户能够探索源于其初始输入的创意和高质量设计。与 DALL-E 3 相比，SCAPE 能够在图像的新颖性上提升 67％，并在质量和使用效果上得到改进；我们展示了 SCAPE 仅经过 3 次迭代，图像的新颖性提高了 24％，能够通过用户进行有效的探索，并优化图像。超过 20 位独立的建筑师对 SCAPE 进行评估，并提供了显著正面的反馈。