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arXiv 2402.00052cs.AIcs.CVcs.GR

用于自动生成建筑方案设计的零样本序列神经-符号推理

Zero-shot Sequential Neuro-symbolic Reasoning for Automatically Generating Architecture Schematic Designs

  • University of Washington(华盛顿大学)
  • WinnDevelopment(温恩开发公司)

机构由 AI 辅助整理,请以论文原文为准。

Milin Kodnongbua, Lawrence H. Curtis, Adriana Schulz

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AI总结:

本研究提出一种基于GPT-4的零样本序列神经-符号推理方法,结合生成式AI与数学规划求解器,模拟传统设计流程自动生成建筑方案设计,无需额外训练,经真实建筑对比验证有效,有望变革建筑方案设计领域。

AI中文摘要:

本文提出了一种用于生成建筑方案设计的新型自动化系统,旨在简化多户住宅房地产开发项目初期的复杂决策过程。该方法结合生成式AI(神经推理)与数学规划求解器(符号推理)的优势,解决了建筑方案设计对专家经验的依赖问题及相关技术挑战。针对整栋建筑设计所需决策规模大、关联性强的特点,我们提出了一种新型序列神经-符号推理方法,模拟从初始概念到详细布局的传统建筑设计流程。为避免手动构建用于近似预期目标的代价函数,我们提出了一种方案:利用神经推理生成约束条件与代价函数,供符号求解器用于求解。我们还在每个设计阶段加入反馈循环,确保神经推理与符号推理紧密结合。该方法基于GPT-4开发,无需额外训练,通过与真实建筑的对比研究验证了其有效性。我们的方法能够结合对周边区域的理解生成多种建筑设计方案,展现出变革建筑方案设计领域的潜力。

英文摘要:

This paper introduces a novel automated system for generating architecture schematic designs aimed at streamlining complex decision-making at the multifamily real estate development project's outset. Leveraging the combined strengths of generative AI (neuro reasoning) and mathematical program solvers (symbolic reasoning), the method addresses both the reliance on expert insights and technical challenges in architectural schematic design. To address the large-scale and interconnected nature of design decisions needed for designing a whole building, we proposed a novel sequential neuro-symbolic reasoning approach, emulating traditional architecture design processes from initial concept to detailed layout. To remove the need to hand-craft a cost function to approximate the desired objectives, we propose a solution that uses neuro reasoning to generate constraints and cost functions that the symbolic solvers can use to solve. We also incorporate feedback loops for each design stage to ensure a tight integration between neuro and symbolic reasoning. Developed using GPT-4 without further training, our method's effectiveness is validated through comparative studies with real-world buildings. Our method can generate various building designs in accordance with the understanding of the neighborhood, showcasing its potential to transform the realm of architectural schematic design.

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