Skip to main content
SpringerLink
Log in

Slime Mold Computing

  • Reference work entry
  • First Online:
Unconventional Computing

Part of the book series: Encyclopedia of Complexity and Systems Science Series ((ECSSS))

  • Originally published in
  • R. A. Meyers (ed.), Encyclopedia of Complexity and Systems Science, © Springer Science+Business Media LLC 2017

Glossary

Physarum polycephalum :

belongs to the order Physarales, subclass Myxogastromycetidae, class Myxomycetes, and division Myxostelida; it is commonly known as a true, acellular, or multiheaded slime mold.

Shortest path :

is a sequence of edges connecting two vertexes in a graph that has a minimal sum of edge weights; in context of the paper, shortest path is determined by sum of distances on Euclidean plane.

Maze :

is a collection of all possible paths between two points.

Travelling salesman problem :

aims to find a shortest path in a graph that visits all nodes and ends in its starting node.

Spanning tree :

of a finite planar set is a connected, undirected, acyclic planar graph, whose vertices are points of the planar set; the tree is a minimal spanning tree where sum of edge lengths is minimal.

Voronoi diagram :

of a set of points is a partition of the plane into such regions that, for any element of the set, a region corresponding to a unique point contains all those points of...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 489.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 599.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Bibliography

  • Adamatzky A (1991) Neural algorithm for constructing minimal spanning tree. Neural Netw World 6:335–339

    Google Scholar 

  • Adamatzky A (2002) Collision-based computing. Springer, London

    Book  Google Scholar 

  • Adamatzky A (2007) Physarum machine: implementation of a Kolmogorov-Uspensky machine on a biological substrate. Parallel Process Lett 17(04):455–467

    Article  MathSciNet  Google Scholar 

  • Adamatzky A (2008) Growing spanning trees in plasmodium machines. Kybernetes 37(2):258–264

    Article  MathSciNet  Google Scholar 

  • Adamatzky A (2009) Developing proximity graphs by Physarum polycephalum: does the plasmodium follow the Toussaint hierarchy? Parallel Process Lett 19(01):105–127

    Article  MathSciNet  Google Scholar 

  • Adamatzky A (2010a) Physarum machines: computers from slime mould. World Scientific Publishing, London

    Google Scholar 

  • Adamatzky A (2010b) Slime mould logical gates: exploring ballistic approach. arXiv preprint arXiv:1005.2301

    Google Scholar 

  • Adamatzky A (2012a) Bioevaluation of world transport networks. World Scientific Publishing, London

    Google Scholar 

  • Adamatzky A (2012b) Slime mold solves maze in one pass, assisted by gradient of chemo- attractants. NanoBioscience IEEE Trans 11(2):131–134

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Adamatzky A (ed) (2016) Advances in Physarum machines: sensing and computing with slime mould. Springer, Heidelberg

    Google Scholar 

  • Adamatzky A, Kayem AVDM (2013) Biological evaluation of trans-African high-ways. European Phys J Spec Top 215(1):49–59

    Article  Google Scholar 

  • Adamatzky A, Martinez GJ (2013) Bio-imitation of Mexican migration routes to the USA with slime mould on 3D terrains. J Bionic Eng 10(2):242–250

    Article  Google Scholar 

  • Adamatzky A, Prokopenko M (2012) Slime mould evaluation of Australian motor- ways. Int J Parallel Emergent Distrib Syst 27(4):275–295

    Article  Google Scholar 

  • Adamatzky A, Schubert T (2012) Schlauschleimer in Reichsautobahnen: slime mould imitates motorway network in Germany. Kybernetes 41(7/8):1050–1071

    Article  Google Scholar 

  • Adamatzky A, Schubert T (2014) Slime mold microfluidic logical gates. Mater Today 17(2):86–91

    Article  Google Scholar 

  • Adamatzky A, De Lacy Costello B, Asai T (2005) Reaction-diffusion computers. Elsevier, Amsterdam

    Google Scholar 

  • Adamatzky A, De Baets B, Van Dessel W (2012) Slime mould imitation of Belgian transport networks: redundancy, bio-essential motorways, and dissolution. Int J Unconv Comput 8(3):235–261

    Google Scholar 

  • Adamatzky A, Akl S, Alonso-Sanz R, Van Dessel W, Ibrahim Z, Ilachinski A, Jones J, Kayem AVDM, Martínez GJ, De Oliveira P et al (2013a) Are motorways rational from slime mould’s point of view? Int J Parallel Emergent Distrib Syst 28(3):230–248

    Article  Google Scholar 

  • Adamatzky A, Lees M, Sloot P (2013b) Bio-development of motorway network in the Netherlands: a slime mould approach. Adv Complex Syst 16(02n03):1250034

    Article  Google Scholar 

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

    Google Scholar 

  • Aono M, Kim S-J, Zhu L, Naruse M, Ohtsu M, Hori H, Hara M (2012). Amoeba-inspired sat solver. In: Proc. NOLTA. p 586–589

    Google Scholar 

  • Aono M, Kasai S, Kim SJ, Wakabayashi M, Miwa H, Naruse M (2015) Amoeba-inspired nanoarchitectonic computing implemented using electrical brownian ratchets. Nanotechnology 26(23):234001

    Article  Google Scholar 

  • Ascher R (1961) Experimental archeology. Am Anthropol 63(4):793–816

    Article  Google Scholar 

  • Becker M, Kromker M, Szczerbicka H (2015) Evaluating heuristic optimiza-tion, bio-inspired and graph-theoretic algorithms for the generation of fault-tolerant graphs with minimal costs. In: Information science and applications. Springer, Berlin, pp 1033–1041

    Chapter  Google Scholar 

  • Blakey E (2014) Towards non-quantum implementations of shor’s factorization algorithm. Int J Unconv Comput 10:339–352

    Google Scholar 

  • Blass A, Gurevich Y (2003) Algorithms: a quest for absolute definitions. Bull EATCS 81:195–225

    MathSciNet  MATH  Google Scholar 

  • Bonifaci V, Mehlhorn K, Varma G (2012) Physarum can compute shortest paths. J Theor Biol 309:121–133

    Article  MathSciNet  Google Scholar 

  • Carlile MJ (1972) The lethal interaction following plasmodial fusion between two strains of the myx-omycete physarum polycephalum. J Gen Microbiol 71(3):581–590

    Article  Google Scholar 

  • Cloteaux B, Ranjan D (2006) Some separation results between classes of pointer algorithms. DCFS 6:232–240

    Google Scholar 

  • Coles J (1979) Experimental archaeology. Academic Press, London

    Google Scholar 

  • Delaunay B (1934) Sur la sphere vide. Izv Akad Nauk SSSR, Otdelenie Matematicheskikh i Estestvennykh Nauk 7(793–800):1–2

    MATH  Google Scholar 

  • Dietrich MR (2015) Explaining the pulse of protoplasm: the search for molecular mechanisms of protoplasmic streaming. J Integr Plant Biol 57(1):14–22

    Article  Google Scholar 

  • Dourvas N, Tsompanas M-A, Sirakoulis GC, Tsalides P (2015) Hardware acceleration of cellular automata Physarum polycephalum model. Parallel Process Lett 25(01):1540006

    Article  MathSciNet  Google Scholar 

  • Durham AC, Ridgway EB (1976) Control of chemotaxis in physarum polycephalum. J Cell Biol 69(1):218–223

    Article  Google Scholar 

  • Edelsbrunner H, Kirkpatrick DG, Seidel R (1983) On the shape of a set of points in the plane. Inf Theory IEEE Trans 29(4):551–559

    Article  MathSciNet  Google Scholar 

  • Evangelidis V, Tsompanas M-A, Sirakoulis GC, Adamatzky A (2015) Slime mould imitates development of Roman roads in the Balkans. J Archaeol Sci Rep 2:264–281

    Google Scholar 

  • Gabriel KR, Sokal RR (1969) A new statistical approach to geographic variation analysis. Syst Biol 18(3):259–278

    Google Scholar 

  • Grebecki A, CieÅ›lawska M (1978) Plasmodium of physarum polycephalum as a synchronous contractile system. Cytobiologie 17(2):335–342

    Google Scholar 

  • Gurevich Y (1988) Kolmogorov machines and related issues. Bull EATCS 35:71–82

    Google Scholar 

  • Hinz AM (1989) The tower of Hanoi. Enseign Math 35(2):289–321

    MathSciNet  MATH  Google Scholar 

  • Hinz AM (1992) Shortest paths between regular states of the Tower of Hanoi. Inf Sci 63(1):173–181

    Article  MathSciNet  Google Scholar 

  • Ingersoll D, Yellen JE, Macdonald W (1977) Experimental archaeology. Columbia University Press, New York

    Google Scholar 

  • Jarvis RA (1973) On the identification of the convex hull of a finite set of points in the plane. Inf Process Lett 2(1):18–21

    Article  Google Scholar 

  • Jones J, Adamatzky A (2010) Towards Physarum binary adders. Biosystems 101(1):51–58

    Article  Google Scholar 

  • Jones J, Adamatzky A (2014a) Computation of the travelling salesman problem by a shrinking blob. Nat Comput 13(1):1–16

    Article  MathSciNet  Google Scholar 

  • Jones J, Adamatzky A (2014b) Material approximation of data smoothing and spline curves inspired by slime mould. Bioinspir Biomim 9(3):036016

    Article  Google Scholar 

  • Kalogeiton VS, Papadopoulos DP, Sirakoulis GC (2014) Hey physarum! Can you perform slam? Int J Unconv Comput 10(4):271–293

    Google Scholar 

  • Kalogeiton VS, Papadopoulos DP, Georgilas IP, Sirakoulis GC, Adamatzky AI (2015a) Biomimicry of crowd evacuation with a slime mould cellular automaton model. In: Computational intelligence, medicine and biology. Springer, Berlin, pp 123–151

    Google Scholar 

  • Kalogeiton VS, Papadopoulos DP, Georgilas IP, Ch Sirakoulis G, Adamatzky AI (2015b) Cellular automaton model of crowd evacuation inspired by slime mould. Int J Gen Syst 44(3):354–391

    Article  MathSciNet  Google Scholar 

  • Kauffman S, Wille JJ (1975) The mitotic oscillator in Physarum polycephalum. J Theor Biol 55(1):47–93

    Article  Google Scholar 

  • Kim S-J, Aono M, Hara M (2010) Tug-of-war model for the two-bandit problem: nonlocally-correlated parallel exploration via resource conservation. Biosystems 101(1):29–36

    Article  Google Scholar 

  • Kishimoto U (1958) Rhythmicity in the protoplasmic streaming of a slime mood, physarum polycephalum. i. A statistical analysis of the electrical potential rhythm. J Gen Physiol 41(6):1205–1222

    Article  Google Scholar 

  • Kolmogorov AN (1953) On the concept of algorithm. Uspekhi Mat Nauk 8(4):175–176

    Google Scholar 

  • Kolmogorov AN, Uspenskii VA (1958) On the definition of an algorithm. Uspekhi Matematicheskikh Nauk 13(4):3–28

    MathSciNet  MATH  Google Scholar 

  • Liang M, Gao C, Liu Y, Tao L, Zhang Z (2015a) A new physarum network based genetic algorithm for bandwidth-delay constrained least-cost multicast routing. In: Advances in swarm and computational intelligence. Springer, Berlin, pp 273–280

    Chapter  Google Scholar 

  • Liang L, Song Y, Zhang H, Ma H, Vasilakos AV (2015b) Physarum optimization: a biology-inspired algorithm for the steiner tree problem in networks. Comput IEEE Trans 64(3):819–832

    MathSciNet  MATH  Google Scholar 

  • MacGregor JN, Ormerod T (1996) Human performance on the traveling salesman problem. Percept Psychophys 580(4):527–539

    Article  Google Scholar 

  • Margolus N (2002) Universal cellular automata based on the collisions of soft spheres. In: Collision-based computing. Springer, London, pp 107–134

    Chapter  Google Scholar 

  • Mayne R, Adamatzky A (2015a) Slime mould foraging behaviour as optically coupled logical operations. Int J Gen Syst 44(3):305–313

    Article  MathSciNet  Google Scholar 

  • Mayne R, Adamatzky A (2015b) On the computing potential of intracellular vesicles. PLoS One 10(10):e0139617

    Article  Google Scholar 

  • Mayne R, Tsompanas M-A, Sirakoulis GC, Adamatzky A (2015) Towards a slime mould-FPGA interface. Biomed Eng Lett 5(1):51–57

    Article  Google Scholar 

  • Miyaji T, Ohnishi I (2008) Physarum can solve the shortest path problem on Riemannian surface mathematically rigorously. Int J Pure Appl Math 47(3):353–369

    MathSciNet  MATH  Google Scholar 

  • Nakagaki T, Yamada H, Toth A (2001) Path finding by tube morphogenesis in an amoeboid organism. Biophys Chem 92(1):47–52

    Article  Google Scholar 

  • Naruse M, Berthel M, Drezet A, Huant S, Aono M, Hori H, Kim S-J (2015) Single-photon decision maker. Sci Rep 5:13253

    Article  Google Scholar 

  • NeÅ¡etÅ™il J, Milková E, NeÅ¡etÅ™ilová H (2001) Otakar Boru°vka on minimum span-ning tree problem translation of both the 1926 papers, comments, history. Discrete Math 233(1):3–36

    Article  MathSciNet  Google Scholar 

  • Piovanelli M, Fujie T, Mazzolai B, Beccai L (2012) A bio-inspired approach towards the development of soft amoeboid microrobots. In: Biomedical Robotics and Biomechatronics (BioRob), 2012 4th IEEE RAS & EMBS International Conference on. IEEE, p 612–616

    Google Scholar 

  • Preparata FP, Shamos MI (1985) Computational geometry: an introduction. Springer, New York

    Book  Google Scholar 

  • Rakoczy L (1963) Application of crossed light and humidity gradients for the investigation of slime-molds. Acta Soc Bot Pol 32(2):393–403

    Article  Google Scholar 

  • Reid CR, Beekman M (2013) Solving the towers of Hanoi—how an amoeboid organism efficiently constructs transport networks. J Exp Biol 216(9):1546–1551

    Article  Google Scholar 

  • Ridgway EB, Durham AC (1976) Oscillations of calcium ion concentrations in Physarum polycephalum. J Cell Biol 69(1):223–226

    Article  Google Scholar 

  • Romik D (2006) Shortest paths in the Tower of Hanoi graph and finite automata. SIAM J Discret Math 20(3):610–622

    Article  MathSciNet  Google Scholar 

  • Saigusa T, Tero A, Nakagaki T, Kuramoto Y (2008) Amoebae anticipate periodic events. Phys Rev Lett 100(1):018101

    Article  Google Scholar 

  • Schön T, Stetter M, Tomé AM, Puntonet CG, Lang EW (2014) Physarum learner: a bio-inspired way of learning structure from data. Expert Syst Appl 41(11):5353–5370

    Article  Google Scholar 

  • Schumann A (2017) Conventional and unconventional reversible logic gates on Physarum polycephalum. International Journal of Parallel, Emergent and Distributed Systems 32(2):218–231

    Google Scholar 

  • Schumann A, Adamatzky A (2011) Physarum spatial logic. New Math Nat Comput 7(03):483–498

    Article  MathSciNet  Google Scholar 

  • Schumann A, Pancerz K, Adamatzky A, Grube M (2014) Bio-inspired game theory: the case of physarum polycephalum. In: Proceedings of the 8th International Conference on Bioinspired Information and Communications Technologies. Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, ICST, p 9–16

    Google Scholar 

  • Shinde Y, Oya T (2014) Design of single-electron slime-mold circuit and its application to solving optimal path planning problem. Nonlinear Theory Appl IEICE 5(s):80–88

    Article  Google Scholar 

  • Shirakawa T, Adamatzky A, Gunji Y-P, Miyake Y (2009) On simultaneous construction of Voronoi diagram and Delaunay triangulation by Physarum polycephalum. Int J Bifurcation Chaos 19(09):3109–3117

    Article  Google Scholar 

  • Shvachko KV (1991) Different modifications of pointer machines and their computational power. In: Mathematical Foundations of Computer Science 1991. Springer, Berlin, pp 426–435

    Chapter  Google Scholar 

  • Stephenson SL, Stempen H, Hall I (1994) Myxomycetes: a handbook of slime molds. Timber Press Portland, Oregon

    Google Scholar 

  • Teplov VA, Romanovsky YM, Latushkin OA (1991) A continuum model of contraction waves and protoplasm streaming in strands of physarum plasmodium. Biosystems 24(4):269–289

    Article  Google Scholar 

  • Tero A, Kobayashi R, Nakagaki T (2006) Physarum solver: a biologically in-spired method of road-network navigation. Phys A: Stat Mech Appl 363(1):115–119

    Article  Google Scholar 

  • Tsompanas M-AI, Mayne R, Sirakoulis GC, Adamatzky AI (2015) A cellular automata bioinspired algorithm designing data trees in wireless sensor networks. Int J Distrib Sens Netw 501:471045

    Article  Google Scholar 

  • Tsuda S, Aono M, Gunji Y-P (2004) Robust and emergent physarum logical-computing. Biosystems 73(1):45–55

    Article  Google Scholar 

  • Ueda T, Muratsugu M, Kurihara K, Kobatake Y (1976) Chemotaxis in Physarum polycephalum: effects of chemicals on isometric tension of the plasmodial strand in relation to chemotactic movement. Exp Cell Res 100(2):337–344

    Article  Google Scholar 

  • Umedachi T, Idei R, Ito K, Ishiguro A (2013) A fluid-filled soft robot that exhibits spontaneous switching among versatile spatiotemporal oscillatory patterns inspired by the true slime mold. Artif Life 19(1):67–78

    Article  Google Scholar 

  • Whiting JGH, de Lacy Costello BPJ, Adamatzky A (2014) Slime mould logic gates based on frequency changes of electrical potential oscillation. Biosystems 124:21–25

    Article  Google Scholar 

  • Wohlfarth-Bottermann KE (1979) Oscillatory contraction activity in physarum. J Exp Biol 81(1):15–32

    Google Scholar 

  • Grigoriev YD (1980) Kolmogoroff algorithms are stronger than turing machines. J Math Sci 14(5):1445–1450

    Article  Google Scholar 

  • Zhang X, Wang Q, Adamatzky A, Chan FT, Mahadevan S, Deng Y (2014) An improved physarum polycephalum algorithm for the shortest path problem. The Scientific World Journal, 2014

    Google Scholar 

  • Zhang, Xiaoge, Sankaran Mahadevan, and Yong Deng. Physarum-inspired applications in graph-optimization problems. Parallel Processing Letters 25.01 (2015): 1540005

    Google Scholar 

  • Zhu L, Aono M, Kim S-J, Hara M (2013) Amoeba-based computing for traveling salesman problem: long-term correlations between spatially separated individual cells of physarum polycephalum. Biosystems 112(1):1–10

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Unconventional Computing Centre, University of the West of England, Bristol, UK

    Andrew Adamatzky

Authors
  1. Andrew Adamatzky
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Andrew Adamatzky .

Editor information

Editors and Affiliations

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

    Andrew Adamatzky

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Adamatzky, A. (2018). Slime Mold Computing. In: Adamatzky, A. (eds) Unconventional Computing. Encyclopedia of Complexity and Systems Science Series. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-6883-1_686

Download citation

Publish with us

Policies and ethics

Search

Navigation