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Inspired by Nature pp 357–387Cite as

Computers from Plants We Never Made: Speculations

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Part of the book series: Emergence, Complexity and Computation ((ECC,volume 28))

Abstract

Plants are highly intelligent organisms. They continuously make distributed processing of sensory information, concurrent decision making and parallel actuation. The plants are efficient green computers per se. Outside in nature, the plants are programmed and hardwired to perform a narrow range of tasks aimed to maximize the plants’ ecological distribution, survival and reproduction. To ‘persuade’ plants to solve tasks outside their usual range of activities, we must either choose problem domains which homomorphic to the plants natural domains or modify biophysical properties of plants to make them organic electronic devices. We discuss possible designs and prototypes of computing systems that could be based on morphological development of roots, interaction of roots, and analog electrical computation with plants, and plant-derived electronic components. In morphological plant processors data are represented by initial configuration of roots and configurations of sources of attractants and repellents; results of computation are represented by topology of the roots’ network. Computation is implemented by the roots following gradients of attractants and repellents, as well as interacting with each other. Problems solvable by plant roots, in principle, include shortest-path, minimum spanning tree, Voronoi diagram, \(\alpha \)-shapes, convex subdivision of concave polygons. Electrical properties of plants can be modified by loading the plants with functional nanoparticles or coating parts of plants of conductive polymers. Thus, we are in position to make living variable resistors, capacitors, operational amplifiers, multipliers, potentiometers and fixed-function generators. The electrically modified plants can implement summation, integration with respect to time, inversion, multiplication, exponentiation, logarithm, division. Mathematical and engineering problems to be solved can be represented in plant root networks of resistive or reaction elements. Developments in plant-based computing architectures will trigger emergence of a unique community of biologists, electronic engineering and computer scientists working together to produce living electronic devices which future green computers will be made of.

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References

  1. Adamatzky, A.: Collision-Based Computing. Springer (2002)

    Google Scholar 

  2. Adamatzky, A.: Hot ice computer. Phys. Lett. A 374(2), 264–271 (2009)

    Article  Google Scholar 

  3. Adamatzky, A.: Physarum Machines: Computers from Slime Mould. World Scientific (2010)

    Google Scholar 

  4. Adamatzky, A.: Slime mould computes planar shapes. Int. J. Bio-Inspir. Comput. 4(3), 149–154 (2012)

    Article  Google Scholar 

  5. Adamatzky, A.: Towards plant wires. Biosystems 122, 1–6 (2014)

    Article  Google Scholar 

  6. Adamatzky, A. (ed.): Advances in Physarum Machines: Sensing and Computing with Slime Mould. Springer (2016)

    Google Scholar 

  7. Adamatzky, A., Armstrong, R., De Lacy Costello, B., Deng, Y., Jones, J., Mayne, R., Schubert, T., Sirakoulis, G.Ch., Zhang, X.: Slime mould analogue models of space exploration and planet colonisation. J. Br. Interplanet. Soc. 67, 290–304 (2014)

    Google Scholar 

  8. Adamatzky, A., Costello, B.D.L., Asai, T.: Reaction-Diffusion Computers. Elsevier (2005)

    Google Scholar 

  9. Adamatzky, A., Holley, J., Bull, L., Costello, B.D.L.: On computing in fine-grained compartmentalised Belousov-Zhabotinsky medium. Chaos Solitons Fractals 44(10), 779–790 (2011)

    Google Scholar 

  10. Adamatzky, A., Kitson, S., Costello, B.D.L., Matranga, M.A., Younger, D.: Computing with liquid crystal fingers: Models of geometric and logical computation. Phys. Rev. E 84(6), 061,702 (2011)

    Google Scholar 

  11. Adamatzky, A., Sirakoulis, G.Ch., Martinez, G.J., Baluska, F., Mancuso, S.: On plant roots logical gates. arXiv preprint arXiv:1610.04602 (2016)

  12. Adleman, L.M., McCurley, K.S.: Open problems in number theoretic complexity, ii. In: International Algorithmic Number Theory Symposium, pp. 291–322. Springer (1994)

    Google Scholar 

  13. Akl, S.G.: Parallel Sorting Algorithms, vol. 12. Academic press (2014)

    Google Scholar 

  14. Bais, H.P., Park, S.W., Weir, T.L., Callaway, R.M., Vivanco, J.M.: How plants communicate using the underground information superhighway. Trends Plant Sci. 9(1), 26–32 (2004)

    Article  Google Scholar 

  15. Bais, H.P., Weir, T.L., Perry, L.G., Gilroy, S., Vivanco, J.M.: The role of root exudates in rhizosphere interactions with plants and other organisms. Annu. Rev. Plant Biol. 57, 233–266 (2006)

    Article  Google Scholar 

  16. Baluška, F., Mancuso, S.: Plant neurobiology as a paradigm shift not only in the plant sciences. Plant Signal. Behav. 2(4), 205–207 (2007)

    Article  Google Scholar 

  17. Baluška, F., Mancuso, S.: Deep evolutionary origins of neurobiology: turning the essence of’neural’upside-down. Commun. Integr. Biol. 2(1), 60–65 (2009)

    Article  Google Scholar 

  18. Baluška, F., Mancuso, S.: Plant neurobiology: from sensory biology, via plant communication, to social plant behavior. Cognit. Process. 10(1), 3–7 (2009)

    Article  Google Scholar 

  19. Baluška, F., Mancuso, S.: Vision in plants via plant-specific ocelli? Trends Plant Sci. 21(9), 727–730 (2016)

    Article  Google Scholar 

  20. Baluška, F., Mancuso, S., Volkmann, D. (eds.): Communication in Plants: Neuronal Aspects of Plant Life. Springer (2007)

    Google Scholar 

  21. Baluška, F., Mancuso, S., Volkmann, D.: Communication in plants. In: Neuronal Aspect of Plant Life. Spriger, Heidelberg (2006)

    Google Scholar 

  22. Baluška, F., Mancuso, S., Volkmann, D., Barlow, P.: Root apices as plant command centres: the unique brain-like status of the root apex transition zone. Biologia (Bratisl.) 59(Suppl. 13), 1–13 (2004)

    Google Scholar 

  23. Baluška, F., Mancuso, S., Volkmann, D., Barlow, P.W.: Root apex transition zone: a signalling-response nexus in the root. Trends Plant Sci. 15(7), 402–408 (2010)

    Article  Google Scholar 

  24. Baluška, F., Volkmann, D., Hlavacka, A., Mancuso, S., Barlow, P.W.: Neurobiological view of plants and their body plan. In: Communication in Plants, pp. 19–35. Springer (2006)

    Google Scholar 

  25. Baluška, F., Volkmann, D., Menzel, D.: Plant synapses: actin-based domains for cell-to-cell communication. Trends Plant Sci. 10(3), 106–111 (2005)

    Article  Google Scholar 

  26. Barlow, P.W.: The response of roots and root systems to their environmentan interpretation derived from an analysis of the hierarchical organization of plant life. Environ. Exp. Bot. 33(1), 1–10 (1993)

    Article  Google Scholar 

  27. Battistoni, S., Dimonte, A., Erokhin, V.: Spectrophotometric characterization of organic memristive devices. Org. Electron. 38, 79–83 (2016)

    Article  Google Scholar 

  28. Battistoni, S., Dimonte, A., Erokhin, V.: Organic memristor based elements for bio-inspired computing. In: Advances in Unconventional Computing, pp. 469–496. Springer (2017)

    Google Scholar 

  29. Bellman, R.: Dynamic programming treatment of the travelling salesman problem. J. ACM (JACM) 9(1), 61–63 (1962)

    Article  MATH  MathSciNet  Google Scholar 

  30. Berzina, T., Erokhin, V., Fontana, M.: Spectroscopic investigation of an electrochemically controlled conducting polymer-solid electrolyte junction. J. Appl. Phys. 101(2), 024,501 (2007)

    Google Scholar 

  31. Birbaum, K., Brogioli, R., Schellenberg, M., Martinoia, E., Stark, W.J., Günther, D., Limbach, L.K.: No evidence for cerium dioxide nanoparticle translocation in maize plants. Environ. Sci. Technol. 44(22), 8718–8723 (2010)

    Article  Google Scholar 

  32. Borghetti, J., Snidera, G.S., Kuekes, P.J., Yang, J.J., Stewart, D.R., Williams, R.S.: Memristive switches enable stateful logic operations via material implication. Nature 464(7290), 873–876 (2010)

    Article  Google Scholar 

  33. Brenner, E.D., Stahlberg, R., Mancuso, S., Vivanco, J., Baluška, F., Van Volkenburgh, E.: Plant neurobiology: an integrated view of plant signaling. Trends Plant Sci. 11(8), 413–419 (2006)

    Article  Google Scholar 

  34. Brockett, R.W.: A rational flow for the Toda lattice equations. In: Operators, Systems and Linear Algebra, pp. 33–44. Springer (1997)

    Google Scholar 

  35. Burbach, C., Markus, K., Zhang, Y., Schlicht, M., Baluška, F.: Photophobic behavior of maize roots. Plant Signal. Behav. 7(7), 874–878 (2012)

    Article  Google Scholar 

  36. Chua, L.: Memristor—the missing circuit element. IEEE Trans. Circuit Theory 18(5), 507–519 (1971)

    Article  Google Scholar 

  37. Chua, L.O., Tseng, C.W.: A memristive circuit model for p-n junction diodes. Int. J. Circuit Theory Appl. 2(4), 367–389 (1974)

    Article  Google Scholar 

  38. Cifarelli, A., Berzina, T., Erokhin, V.: Bio-organic memristive device: polyaniline–physarum polycephalum interface. Phys. Status Solidi (c) 12(1-2), 218–221 (2015)

    Google Scholar 

  39. Ciszak, M., Comparini, D., Mazzolai, B., Baluska, F., Arecchi, F.T., Vicsek, T., Mancuso, S.: Swarming behavior in plant roots. PLoS One 7(1), e29,759 (2012)

    Google Scholar 

  40. Costello, B.D.L., Adamatzky, A.: Experimental implementation of collision-based gates in Belousov-Zhabotinsky medium. Chaos Solitons Fractals 25(3), 535–544 (2005)

    Google Scholar 

  41. Costello, B.D.L., Adamatzky, A., Jahan, I., Zhang, L.: Towards constructing one-bit binary adder in excitable chemical medium. Chem. Phys. 381(1), 88–99 (2011)

    Article  Google Scholar 

  42. Demin, V., Erokhin, V., Emelyanov, A., Battistoni, S., Baldi, G., Iannotta, S., Kashkarov, P., Kovalchuk, M.: Hardware elementary perceptron based on polyaniline memristive devices. Org. Electron. 25, 16–20 (2015)

    Article  Google Scholar 

  43. DeWeese, M.R., Zador, A.: Neurobiology: efficiency measures. Nature 439(7079), 920–921 (2006)

    Article  Google Scholar 

  44. Dimonte, A., Battistoni, S., Erokhin, V.: Physarum in hybrid electronic devices. In: Advances in Physarum Machines, pp. 91–107. Springer (2016)

    Google Scholar 

  45. Dowling, W.F., Gallier, J.H.: Linear-time algorithms for testing the satisfiability of propositional horn formulae. J. Log. Program. 1(3), 267–284 (1984)

    Article  MATH  MathSciNet  Google Scholar 

  46. Emelyanov, A., Lapkin, D., Demin, V., Erokhin, V., Battistoni, S., Baldi, G., Dimonte, A., Korovin, A., Iannotta, S., Kashkarov, P., et al.: First steps towards the realization of a double layer perceptron based on organic memristive devices. AIP Adv. 6(11), 111,301 (2016)

    Google Scholar 

  47. Erokhin, V., Berzina, T., Camorani, P., Fontana, M.P.: Non-equilibrium electrical behaviour of polymeric electrochemical junctions. J. Phys. Condens. Matter 19(20), 205,111 (2007)

    Google Scholar 

  48. Erokhin, V., Berzina, T., Camorani, P., Smerieri, A., Vavoulis, D., Feng, J., Fontana, M.P.: Material memristive device circuits with synaptic plasticity: learning and memory. BioNanoScience 1(1–2), 24–30 (2011)

    Article  Google Scholar 

  49. Erokhin, V., Fontana, M.P.: Electrochemically controlled polymeric device: a memristor (and more) found two years ago. arXiv preprint arXiv:0807.0333 (2008)

  50. Erokhin, V., Howard, G.D., Adamatzky, A.: Organic memristor devices for logic elements with memory. Int. J. Bifurcat. Chaos 22(11), 1250,283 (2012)

    Google Scholar 

  51. Felle, H.H., Zimmermann, M.R.: Systemic signalling in barley through action potentials. Planta 226(1), 203–214 (2007)

    Article  Google Scholar 

  52. Fredkin, E., Toffoli, T.: Conservative logic. In: A. Adamatzky (ed.) Collision-Based Computing. Springer (2002)

    Google Scholar 

  53. Fromm, J., Lautner, S.: Electrical signals and their physiological significance in plants. Plant Cell Environ. 30(3), 249–257 (2007)

    Article  Google Scholar 

  54. Gács, P., Kurdyumov, G.L., Levin, L.A.: One-dimensional uniform arrays that wash out finite islands. Probl. Peredachi Informatsii 14(3), 92–96 (1978)

    Google Scholar 

  55. Gagliano, M., Mancuso, S., Robert, D.: Towards understanding plant bioacoustics. Trends Plant Sci 17(6), 323–325 (2012)

    Article  Google Scholar 

  56. Gagliano, M., Renton, M., Depczynski, M., Mancuso, S.: Experience teaches plants to learn faster and forget slower in environments where it matters. Oecologia 175(1), 63–72 (2014)

    Article  Google Scholar 

  57. Gagliano, M., Renton, M., Duvdevani, N., Timmins, M., Mancuso, S.: Acoustic and magnetic communication in plants: is it possible? Plant Signal Behav 7(10), 1346–1348 (2012)

    Article  Google Scholar 

  58. Gale, E., Adamatzky, A., de Lacy Costello, B.: Slime mould memristors. BioNanoScience 5(1), 1–8 (2015)

    Google Scholar 

  59. Gao, L., Alibart, F., Strukov, D.B.: Programmable cmos/memristor threshold logic. IEEE Trans. Nanotechnol. 12(2), 115–119 (2013)

    Article  Google Scholar 

  60. Geddes, L., Baker, L.: The specific resistance of biological materiala compendium of data for the biomedical engineer and physiologist. Med. Biol. Eng. 5(3), 271–293 (1967)

    Article  Google Scholar 

  61. Gizzie, N., Mayne, R., Patton, D., Kendrick, P., Adamatzky, A.: On hybridising lettuce seedlings with nanoparticles and the resultant effects on the organisms electrical characteristics. Biosystems 147, 28–34 (2016)

    Article  Google Scholar 

  62. Graham, T.L.: Flavonoid and isoflavonoid distribution in developing soybean seedling tissues and in seed and root exudates. Plant Physiol. 95(2), 594–603 (1991)

    Article  Google Scholar 

  63. Gunji, Y.P., Nishiyama, Y., Adamatzky, A., Simos, T.E., Psihoyios, G., Tsitouras, C., Anastassi, Z.: Robust soldier crab ball gate. Complex systems 20(2), 93 (2011)

    Google Scholar 

  64. Harding, S., Koutnik, J., Greff, K., Schmidhuber, J., Adamatzky, A.: Discovering Boolean gates in slime mould. arXiv preprint arXiv:1607.02168 (2016)

  65. James, M.L., Smith, G.M., Wolford, J.C.: Analog computer simulation of engineering systems. International Textbook Company (1966)

    Google Scholar 

  66. Johnson, C.L.: Analog Computer Techniques. McGraw-Hill Book Company, Incorporated (1963)

    Google Scholar 

  67. Kalmar, L., Suranyi, J.: On the reduction of the decision problem. J. Symb. Log. 12(03), 65–73 (1947)

    Article  MATH  Google Scholar 

  68. Kosta, S.P., Kosta, Y., Bhatele, M., Dubey, Y., Gaur, A., Kosta, S., Gupta, J., Patel, A., Patel, B.: Human blood liquid memristor. Int. J. Med. Eng. Inform. 3(1), 16–29 (2011)

    Article  Google Scholar 

  69. Kvatinsky, S., Belousov, D., Liman, S., Satat, G., Wald, N., Friedman, E.G., Kolodny, A., Weiser, U.C.: MAGIC - memristor-aided logic. IEEE Trans. Circuits Syst. 61-II(11), 895–899 (2014)

    Google Scholar 

  70. Kvatinsky, S., Wald, N., Satat, G., Kolodny, A., Weiser, U.C., Friedman, E.G.: Mrl—memristor ratioed logic. In: 2012 13th International Workshop on Cellular Nanoscale Networks and their Applications, pp. 1–6 (2012)

    Google Scholar 

  71. Lehtonen, E., Tissari, J., Poikonen, J.H., Laiho, M., Koskinen, L.: A cellular computing architecture for parallel memristive stateful logic. Microelectron. J. 45(11), 1438–1449 (2014)

    Article  Google Scholar 

  72. Linn, E., Rosezin, R., Tappertzhofen, S., Bttger, U., Waser, R.: Beyond von Neumann logic operations in passive crossbar arrays alongside memory operations. Nanotechnology 23(30), 305,205 (2012)

    Google Scholar 

  73. Lykkebø, O.R., Harding, S., Tufte, G., Miller, J.F.: MECOBO: A hardware and software platform for in materio evolution. In: International Conference on Unconventional Computation and Natural Computation, pp. 267–279. Springer (2014)

    Google Scholar 

  74. Lykkebø, O.R., Nichele, S., Tufte, G.: An investigation of square waves for evolution in carbon nanotubes material. In: 13th European Conference on Artificial Life (2015)

    Google Scholar 

  75. Mancuso, S.: Hydraulic and electrical transmission of wound-induced signals in vitis vinifera. Funct. Plant Biol. 26(1), 55–61 (1999)

    Google Scholar 

  76. Mancuso, S.: Seasonal dynamics of electrical impedance parameters in shoots and leaves related to rooting ability of olive (Olea europea) cuttings. Tree Physiol. 19(2), 95–101 (1999)

    Article  Google Scholar 

  77. Martinsen, Ø.G., Grimnes, S., Lütken, C., Johnsen, G.: Memristance in human skin. In: Journal of Physics: Conference Series, vol. 224, p. 012071. IOP Publishing (2010)

    Google Scholar 

  78. Masi, E., Ciszak, M., Stefano, G., Renna, L., Azzarello, E., Pandolfi, C., Mugnai, S., Baluška, F., Arecchi, F., Mancuso, S.: Spatiotemporal dynamics of the electrical network activity in the root apex. Proc. Natl. Acad. Sci. 106(10), 4048–4053 (2009)

    Article  Google Scholar 

  79. Massey, M., Kotsialos, A., Qaiser, F., Zeze, D., Pearson, C., Volpati, D., Bowen, L., Petty, M.: Computing with carbon nanotubes: Optimization of threshold logic gates using disordered nanotube/polymer composites. J. Appl. Phys. 117(13), 134,903 (2015)

    Google Scholar 

  80. Miller, J.F., Harding, S.L., Tufte, G.: Evolution-in-materio: evolving computation in materials. Evol. Intell. 7(1), 49–67 (2014)

    Article  Google Scholar 

  81. Mills, J.: Kirchhoff-Lukasiewicz Machines. Indiana University Web Sites Collection. (1995)

    Google Scholar 

  82. Mills, J.W.: The nature of the extended analog computer. Phys. D. 237(9), 1235–1256 (2008)

    Google Scholar 

  83. Morgan, A.J., Barrow, D.A., Adamatzky, A., Hanczyc, M.M.: Simple fluidic digital half-adder. arXiv preprint arXiv:1602.01084 (2016)

  84. Ore, O.: Note on Hamilton circuits. Am. Math. Mon. 67(1), 55–55 (1960)

    Google Scholar 

  85. Papandroulidakis, G., Vourkas, I., Vasileiadis, N., Sirakoulis, G.Ch.: Boolean logic operations and computing circuits based on memristors. IEEE Trans. Circuits Syst. II Express Br. 61(12), 972–976 (2014)

    Google Scholar 

  86. Perel’man, M.E., Rubinstein, G.M.: Ultrasound vibrations of plant cells membranes: water lift in trees, electrical phenomena. arXiv:preprint physics/0611133 (2006)

    Google Scholar 

  87. Pershin, Y.V., Ventra, M.D.: Neuromorphic, digital, and quantum computation with memory circuit elements. Proc. IEEE 100(6), 2071–2080 (2012)

    Article  Google Scholar 

  88. Peterson, G.R.: Basic Analog Computation. Macmillan (1967)

    Google Scholar 

  89. Schlicht, M., Ludwig-Müller, J., Burbach, C., Volkmann, D., Baluska, F.: Indole-3-butyric acid induces lateral root formation via peroxisome-derived indole-3-acetic acid and nitric oxide. New Phytol. 200(2), 473–482 (2013)

    Article  Google Scholar 

  90. Semiconductor Industry Association: International Technology Roadmap for Semiconductors (ITRS). Semiconductor Industry Association (2007). http://www.itrs2.net

  91. Soroka, W.W.: Analog Methods in Computation and Simulation. McGraw-Hill (1954)

    Google Scholar 

  92. Steinkellner, S., Lendzemo, V., Langer, I., Schweiger, P., Khaosaad, T., Toussaint, J.P., Vierheilig, H.: Flavonoids and strigolactones in root exudates as signals in symbiotic and pathogenic plant-fungus interactions. Molecules 12(7), 1290–1306 (2007)

    Article  Google Scholar 

  93. Stone, B.B., Esmon, C.A., Liscum, E.: Phototropins, other photoreceptors, and associated signaling: the lead and supporting cast in the control of plant movement responses. Curr. Top. Dev. Biol. 66, 215–238 (2005)

    Article  Google Scholar 

  94. Strukov, D.B., Snider, G.S., Stewart, D.R., Williams, R.S.: The missing memristor found. Nature 453(7191), 80–83 (2008)

    Article  Google Scholar 

  95. Sugiyama, A., Yazaki, K.: Root exudates of legume plants and their involvement in interactions with soil microbes. In: Secretions and exudates in biological systems, pp. 27–48. Springer (2012)

    Google Scholar 

  96. Tarabella, G., D’Angelo, P., Cifarelli, A., Dimonte, A., Romeo, A., Berzina, T., Erokhin, V., Iannotta, S.: A hybrid living/organic electrochemical transistor based on the Physarum polycephalum cell endowed with both sensing and memristive properties. Chem. Sci. 6(5), 2859–2868 (2015)

    Google Scholar 

  97. Trewavas, A.: Green plants as intelligent organisms. Trends Plant Sci. 10(9), 413–419 (2005)

    Article  Google Scholar 

  98. Trewavas, A.: What is plant behaviour? Plant Cell Environ. 32(6), 606–616 (2009)

    Article  Google Scholar 

  99. Trewavas, A.J., Baluška, F.: The ubiquity of consciousness. EMBO Rep. 12(12), 1221–1225 (2011)

    Article  Google Scholar 

  100. Volkov, A.G.: Electrophysiology and phototropism. In: Communication in Plants, pp. 351–367. Springer (2006)

    Google Scholar 

  101. Volkov, A.G., Ranatunga, D.R.A.: Plants as environmental biosensors. Plant Signal. Behav. 1(3), 105–115 (2006)

    Article  Google Scholar 

  102. Volkov, A.G., Tucket, C., Reedus, J., Volkova, M.I., Markin, V.S., Chua, L.: Memristors in plants. Plant Signal. Behav. 9(3), e28,152 (2014)

    Google Scholar 

  103. Vourkas, I., Sirakoulis, G.Ch.: Memristor-based combinational circuits: a design methodology for encoders/decoders. Microelectron. J. 45(1), 59–70 (2014)

    Google Scholar 

  104. Vourkas, I., Sirakoulis, G.Ch.: Emerging memristor-based logic circuit design approaches: a review. IEEE Circuits Syst. Mag. 16(3), 15–30 (2016)

    Google Scholar 

  105. Vourkas, I., Sirakoulis, G.Ch.: Memristor-based nanoelectronic computing circuits and architectures. In: Emergence Complexity and Computation. Springer, Cham (2016)

    Google Scholar 

  106. Weyrick, R.C.: Fundamentals of Analog Computers. Prentice Hall (1969)

    Google Scholar 

  107. Xu, W., Ding, G., Yokawa, K., Baluška, F., Li, Q.F., Liu, Y., Shi, W., Liang, J., Zhang, J.: An improved agar-plate method for studying root growth and response of Arabidopsis thaliana. Sci. Rep. 3, 1273 (2013)

    Google Scholar 

  108. Yokawa, K., Baluska, F.: Binary decisions in maize root behavior: Y-maze system as tool for unconventional computation in plants. IJUC 10(5–6), 381–390 (2014)

    Google Scholar 

  109. Yokawa, K., Kagenishi, T., Kawano, T., Mancuso, S., Baluška, F.: Illumination of arabidopsis roots induces immediate burst of ros production. Plant Signal. Behav. 6(10), 1460–1464 (2011)

    Article  Google Scholar 

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Authors and Affiliations

  1. Unconventional Computing Centre, UWE, Bristol, UK

    Andrew Adamatzky, Simon Harding, Richard Mayne & Nina Gizzie

  2. CNR-IMEM, Parma, Italy

    Victor Erokhin

  3. Institute of Cellular and Molecular Botany, University of Bonn, Bonn, Germany

    Frantisek Baluška

  4. International Laboratory of Plant Neurobiology, University of Florence, Firenze, Italy

    Stefano Mancuso

  5. Department of Electrical & Computer Engineering, Democritus University of Thrace, Xanthi, Greece

    Georgios Ch. Sirakoulis

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  1. Andrew Adamatzky
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  1. Department of Computer Science, University of York, York, United Kingdom

    Susan Stepney

  2. Unconventional Computing Centre, University of the West of England, Bristol, United Kingdom

    Andrew Adamatzky

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Adamatzky, A. et al. (2018). Computers from Plants We Never Made: Speculations. In: Stepney, S., Adamatzky, A. (eds) Inspired by Nature. Emergence, Complexity and Computation, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-67997-6_17

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