Self-organizing computation a framework for generative approaches to architectural design
Self-organizing computation a framework for generative approaches to architectural design
复制标题
自组织计算建筑设计生成方法的框架
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
Taro Narahara
中科院分区：
文献类型：
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作者：
M. Bechthold;Taro Narahara
本文提出了自组织逻辑在产生式设计系统中应用的概念框架。本文介绍的方法是一种抽象和概念性的形式，探索了计算设计策略的一个可能的未来方向。为了解释这一解决问题的方向的潜力，我们将讨论我们当代建筑和城市设计实践所面临的总体方面，以回应我们文化中日益复杂的问题。然而，这篇论文的主要焦点并不是提供即时解决方法来解决当代建筑中的任何具体专业问题。相反，本文研究了这种方法的新兴特征，它可能随着时间的推移而演变出新的设计解决方案，并展示了如何使用该方法的工具与人类进行设计协作，而不是简单地作为被动的评估和分析工具。论文预见了这一受自组织计算(SOC)启发的新设计方向的重要潜力，并对其在建筑和城市设计中的潜在应用领域进行了推测。
近年来，许多科学家已经开始通过他们在电信网络和机器人等领域的计算模型来获得自然界中自组织系统的优势。这种系统的主要优点是健壮性、灵活性、适应性、并发性和分布性。
SOC的一个独特特点是它不依赖任何外部知识。与建筑中的许多传统计算方法一样，当一个人想要有效地推导出似乎是我们认识的主题时，施加现有的设计模式或转换序列是有益的。然而，依赖预先存在的模板可能会排除发现原始输入自然变成什么的可能性。
SOC是一种计算方法，它展示了自组织系统的动态机制的优势：结构出现在系统的全局级别上，来自其较低级别组件之间的相互作用。为了在计算上实现这些机制，需要描述系统的组成单元(子单元)和定义其交互(行为)的规则。该系统期望全球范围的空间结构从其自身组成部分的本地定义的相互作用中出现。
This thesis proposes a conceptual framework for applications of self-organizing logics in generative design systems. The methods introduced in this thesis are in an abstract and conceptual form that explores one possible future direction of computational design strategy. In order to explain the potential of this problem-solving direction, general aspects of what our contemporary practice in architecture and urban design is facing will be discussed in response to the increasing complexity in our culture. However, the main focus of this thesis is not on providing immediate solution methods to resolve any specific professional problems in contemporary architecture. Rather, the thesis investigates the emergent characteristics of this method that can potentially evolve new design solutions over time, and shows how tools employing the method can be used for design collaboration with humans, rather than simply as passive evaluation and analysis tools. The thesis foresees important potential for this new design direction inspired by self-organizing computation (SOC) and speculates regarding its potential areas of application in architecture and urban design.
In recent years, many scientists have started to gain the advantages of self-organizing systems in nature through their computational models in areas such as telecommunication networks and robotics. Main advantages of such systems are robustness, flexibility, adaptability, concurrency, and distributedness.
One of the unique characteristics of SOC is its non-reliance on any external knowledge. As with many conventional computational methods in architecture, imposing existing design patterns or transformation sequences is beneficial when one wants to efficiently derive what appear to be the subjects of our recognitions. However, reliance on a pre-existing template might preclude the possibility of discovering what original inputs naturally turn into.
SOC is a computational approach that brings out the strengths of the dynamic mechanisms of self-organizing systems: structures appear at the global level of a system from interactions among its lower-level components. In order to computationally implement the mechanisms, the system’s constituent units (subunits) and the rules that define their interactions (behaviors) need to be described. The system expects emergence of global-scale spatial structures from the locally defined interactions of its own components.