In recent days, self-assembling swarm robots have been studied by a number of researchers due to their advantages such as high efficiency, stability, and scalability. However, there are still critical issues in applying them to practical problems in the real world. The main objective of this study is to develop a novel self-assembling swarm robot algorithm that overcomes the limitations of existing approaches. To this end, multitree genetic programming is newly designed to efficiently discover a set of patterns necessary to carry out the mission of the self-assembling swarm robots. The obtained patterns are then incorporated into their corresponding robot modules. The computational experiments prove the effectiveness of the proposed approach.
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http://dx.doi.org/10.1155/2013/593848 | DOI Listing |
Entropy (Basel)
June 2024
Allen Discovery Center, Tufts University, Medford, MA 02155, USA.
In recent years, the scientific community has increasingly recognized the complex multi-scale competency architecture (MCA) of biology, comprising nested layers of active homeostatic agents, each forming the self-orchestrated substrate for the layer above, and, in turn, relying on the structural and functional plasticity of the layer(s) below. The question of how natural selection could give rise to this MCA has been the focus of intense research. Here, we instead investigate the effects of such decision-making competencies of MCA agential components on the process of evolution itself, using in silico neuroevolution experiments of simulated, minimal developmental biology.
View Article and Find Full Text PDFJ Chem Phys
February 2024
School of Molecular Sciences and Center for Molecular Design and Biomimetics, The Biodesign Institute, Arizona State University, 1001 South McAllister Avenue, Tempe, Arizona 85281, USA.
We introduce an allostery-mimetic building block model for the self-assembly of 3D structures. We represent the building blocks as patchy particles, where each binding site (patch) can be irreversibly activated or deactivated by binding of the particle's other controlling patches to another particle. We show that these allostery-mimetic systems can be designed to increase yields of target structures by disallowing misassembled states and can further decrease the smallest number of distinct species needed to assemble a target structure.
View Article and Find Full Text PDFEur Phys J E Soft Matter
September 2021
Department of Chemical Engineering and Materials Science, University of Minnesota - Twin Cities, 421 Washington Avenue SE, Minneapolis, MN, 55455, USA.
Facile exploration of large design spaces is critical to the development of new functional soft materials, including self-assembling block polymers, and computational inverse design methodologies are a promising route to initialize this task. We present here an open-source software package coupling particle swarm optimization (PSO) with an existing open-source self-consistent field theory (SCFT) software for the inverse design of self-assembling block polymers to target bulk morphologies. To lower the barrier to use of the software and facilitate exploration of novel design spaces, the underlying SCFT calculations are seeded with algorithmically generated initial fields for four typical morphologies: lamellae, network phases, cylindrical phases, and spherical phases.
View Article and Find Full Text PDFRSC Adv
October 2020
Department of Materials Science, Fudan University Shanghai 200433 China
Nano/-micromotors self-assembling into static and dynamic clusters are of considerable promise to study smart, interactive, responsive, and adaptive nano/-micromaterials that can mimic spatio-temporal patterns, swarming, and collective behaviors widely observed in nature. Previously, the dynamic self-assembly of bubble-propelled catalytic micromotors initiated by capillary forces has been reported. This manuscript shows novel self-assembly modes of magnetic/catalytic Ti/FeNi/Pt tubular micromotors.
View Article and Find Full Text PDFMicromachines (Basel)
July 2018
Department of Ocean Mechanical Engineering, National Fisheries University, Shimonoseki 759-6595, Japan.
The basic rules of self-organization using a totalistic cellular automaton (CA) were investigated, for which the cell state was determined by summing the states of neighboring cells, like in Conway's Game of Life. This study used a short-range and long-range summation of the cell states around the focal cell. These resemble reaction-diffusion (RD) equations, in which self-organizing behavior emerges from interactions between an activating factor and an inhibiting factor.
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