The structural power of reconfigurable circuits in the amoebot model

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Natural Computing Pub Date : 2024-04-13 DOI:10.1007/s11047-024-09981-6
Andreas Padalkin, Christian Scheideler, Daniel Warner
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Abstract

The amoebot model (Derakhshandeh et al. in: SPAA ACM, pp 220–222. https://doi.org/10.1145/2612669.2612712, 2014) has been proposed as a model for programmable matter consisting of tiny, robotic elements called amoebots. We consider the reconfigurable circuit extension (Feldmann et al. in J Comput Biol 29(4):317–343. https://doi.org/10.1089/cmb.2021.0363, 2022) of the geometric amoebot model that allows the amoebot structure to interconnect amoebots by so-called circuits. A circuit permits the instantaneous transmission of signals between the connected amoebots. In this paper, we examine the structural power of the reconfigurable circuits. We start with fundamental problems like the stripe computation problem where, given any connected amoebot structure S, an amoebot u in S, and some axis X, all amoebots belonging to axis X through u have to be identified. Second, we consider the global maximum problem, which identifies an amoebot at the highest possible position with respect to some direction in some given amoebot (sub)structure. A solution to this problem can be used to solve the skeleton problem, where a cycle of amoebots has to be found in the given amoebot structure which contains all boundary amoebots. A canonical solution to that problem can be used to come up with a canonical path, which provides a unique characterization of the shape of the given amoebot structure. Constructing canonical paths for different directions allows the amoebots to set up a spanning tree and to check symmetry properties of the given amoebot structure. The problems are important for a number of applications like rapid shape transformation, energy dissemination, and structural monitoring. Interestingly, the reconfigurable circuit extension allows polylogarithmic-time solutions to all of these problems.

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变形虫模型中可重构电路的结构力
阿米巴机器人模型(Derakhshandeh et al:SPAA ACM, pp 220-222. https://doi.org/10.1145/2612669.2612712, 2014)已被提出作为可编程物质的模型,该模型由被称为变形虫的微小机器人元件组成。我们考虑的是几何变形虫模型的可重构电路扩展(Feldmann 等人,载于:J Comput Biol 29(4):317-343. https://doi.org/10.1089/cmb.2021.0363, 2022),它允许变形虫结构通过所谓的电路将变形虫相互连接起来。电路允许在连接的变形虫之间瞬时传输信号。在本文中,我们将研究可重构电路的结构能力。我们从基本问题入手,如条纹计算问题,即给定任何连接的变形机器人结构 S、S 中的变形机器人 u 和某个轴 X,必须识别出通过 u 属于轴 X 的所有变形机器人。其次,我们考虑全局最大值问题,即在给定的阿米机器人(子)结构中,确定一个阿米机器人相对于某个方向的最高位置。这个问题的解可以用来解决骨架问题,即必须在给定的变形机器人结构中找到一个包含所有边界变形机器人的变形机器人循环。该问题的规范解可以用来得出规范路径,它为给定变形机器人结构的形状提供了唯一的特征。通过构建不同方向的典型路径,阿米机器人可以建立生成树,并检查给定阿米机器人结构的对称性。这些问题对于快速形状转换、能量传播和结构监测等许多应用都非常重要。有趣的是,可重构电路扩展允许对所有这些问题进行多对数时间求解。
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来源期刊
Natural Computing
Natural Computing Computer Science-Computer Science Applications
CiteScore
4.40
自引率
4.80%
发文量
49
审稿时长
3 months
期刊介绍: The journal is soliciting papers on all aspects of natural computing. Because of the interdisciplinary character of the journal a special effort will be made to solicit survey, review, and tutorial papers which would make research trends in a given subarea more accessible to the broad audience of the journal.
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