Collaborative Computation in Self-Organizing Particle Systems
Collaborative Computation in Self-Organizing Particle Systems
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DOI：
10.1007/978-3-319-92435-9_14
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发表时间：
2017-10
期刊：
影响因子：
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通讯作者：
Alexandra M. Porter;A. Richa
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文献类型：
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作者：
Alexandra M. Porter;A. Richa
已经提出了许多形式的可编程物质用于各种任务。我们使用一个抽象的模型，自组织粒子系统的可编程物质，可用于各种应用，包括智能涂料和涂料工程或可编程细胞用于医疗用途。使用该模型的先前研究集中在形状形成和其他空间配置问题（例如，包衣和压制）。在这项工作中，我们研究的基础计算任务，超过了一个粒子的个人恒定大小的内存的能力，如实现计数器和矩阵向量乘法。这些任务代表了使用这些自组织系统的新方法，这些方法与以前的形状和配置工作相结合，使系统可用于更广泛的任务。它们还可以利用自组织系统的分布式和动态特性，使其比传统的线性计算硬件更高效和适应性更强。最后，我们展示了类似类型的计算与自组织系统的图像处理的应用程序，实现图像颜色变换和边缘检测算法。
Many forms of programmable matter have been proposed for various tasks. We use an abstract model of self-organizing particle systems for programmable matter which could be used for a variety of applications, including smart paint and coating materials for engineering or programmable cells for medical uses. Previous research using this model has focused on shape formation and other spatial configuration problems (e.g., coating and compression). In this work we study foundational computational tasks that exceed the capabilities of the individual constant size memory of a particle, such as implementing a counter and matrix-vector multiplication. These tasks represent new ways to use these self-organizing systems, which, in conjunction with previous shape and configuration work, make the systems useful for a wider variety of tasks. They can also leverage the distributed and dynamic nature of the self-organizing system to be more efficient and adaptable than on traditional linear computing hardware. Finally, we demonstrate applications of similar types of computations with self-organizing systems to image processing, with implementations of image color transformation and edge detection algorithms.