Bio-inspired computing tissues: towards machines that evolve, grow, and learn

被引:22
|
作者
Teuscher, C [1 ]
Mange, D [1 ]
Stauffer, A [1 ]
Tempesti, G [1 ]
机构
[1] Ecole Polytech Fed Lausanne, Swiss Fed Inst Technol, Log Syst Lab, CH-1015 Lausanne, Switzerland
关键词
tissue; growth; evolution; learning; BioWatch; BioWall; embryonics;
D O I
10.1016/S0303-2647(02)00100-4
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Biological inspiration in the design of computing machines could allow the creation of new machines with promising characteristics such as fault-tolerance, self-replication or cloning, reproduction, evolution, adaptation and learning, and growth. The aim of this paper is to introduce bio-inspired computing tissues that might constitute a key concept for the implementation of 'living' machines. We first present a general overview of bio-inspired systems and the POE model that classifies bio-inspired machines along three axes. The Embryonics project-inspired by some of the basic processes of molecular biology-is described by means of the BioWatch application, a fault-tolerant and self-repairable watch. The main characteristics of the Embryonics project are the multicellular organization, the cellular differentiation, and the self-repair capabilities. The BioWall is intended as a reconfigurable computing tissue, capable of interacting with its environment by means of a large number of touch-sensitive elements coupled with a color display. For illustrative purposes, a large-scale implementation of the BioWatch on the BioWall's computational tissue is presented. We conclude the paper with a description of bio-inspired computing tissues and POEtic machines. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.
引用
收藏
页码:235 / 244
页数:10
相关论文
共 50 条
  • [1] Book Review: Bio-Inspired Computing Machines: Towards Novel Computational Architectures
    Garrison W. Greenwood
    [J]. Genetic Programming and Evolvable Machines, 2001, 2 (1) : 75 - 78
  • [2] Bio-inspired computing machines with self-repair mechanisms
    Stauffer, A
    Mange, D
    Tempesti, G
    [J]. BIOLOGICALLY INSPIRED APPROACHES TO ADVANCED INFORMATION TECHNOLOGY, PROCEEDINGS, 2006, 3853 : 128 - 140
  • [3] Bio-Inspired Computing, Information Swarms, and the Problem of Data Fusion Bio-Inspired Computing
    Nordmann, Brian
    [J]. TECHNOLOGICAL INNOVATIONS IN SENSING AND DETECTION OF CHEMICAL, BIOLOGICAL, RADIOLOGICAL, NUCLEAR THREATS AND ECOLOGICAL TERRORISM, 2012, : 35 - 44
  • [4] Bio-Inspired Computing and Communication
    Crowcroft, Jon
    [J]. BIO-INSPIRED COMPUTING AND COMMUNICATION, 2008, 5151 : 1 - 8
  • [5] BIO-INSPIRED ENGINEERING Manta Machines
    Pennisi, Elizabeth
    [J]. SCIENCE, 2011, 332 (6033) : 1028 - 1029
  • [6] Molecular machines with bio-inspired mechanisms
    Zhang, Liang
    Marcos, Vanesa
    Leigh, David A.
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2018, 115 (38) : 9397 - 9404
  • [7] Bio-inspired computing paradigms (natural computing)
    Paun, G
    [J]. UNCONVENTIONAL PROGRAMMING PARADIGMS, 2005, 3566 : 155 - 160
  • [8] Parameterized Analysis of Bio-inspired Computing
    Neumann, Frank
    [J]. 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2017,
  • [9] Bio-inspired computing: constituents and challenges
    Akerkar, Rajendra
    Sajja, Priti Srinivas
    [J]. INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION, 2009, 1 (03) : 135 - 150
  • [10] Bio-inspired molecular machines and their biological applications
    Tasbas, Mehmed Nazif
    Sahin, Emin
    Erbas-Cakmak, Sundus
    [J]. COORDINATION CHEMISTRY REVIEWS, 2021, 443