Emergence, Complexity and Computation ECC Jeff Jones From Pattern Formation to Material Computation Multi-agent Modelling of Physarum Polycephalum Emergence, Complexity and Computation Volume 15 Serieseditors IvanZelinka,TechnicalUniversityofOstrava,Ostrava,CzechRepublic e-mail:[email protected] AndrewAdamatzky,UniversityoftheWestofEngland,Bristol,UnitedKingdom e-mail:[email protected] GuanrongChen,CityUniversityofHongKong,HongKong e-mail:[email protected] EditorialBoard AjithAbraham,MirLabs,USA AnaLuciaC.Bazzan,UniversidadeFederaldoRioGrandedoSul,PortoAlegre RSBrasil JuanC.Burguillo,UniversityofVigo,Spain SergejCˇelikovský,AcademyofSciencesoftheCzechRepublic,CzechRepublic MohammedChadli,UniversityofJulesVerne,France EmilioCorchado,UniversityofSalamanca,Spain DonaldDavendra,TechnicalUniversityofOstrava,CzechRepublic AndrewIlachinski,CenterforNavalAnalyses,USA JouniLampinen,UniversityofVaasa,Finland MartinMiddendorf,UniversityofLeipzig,Germany EdwardOtt,UniversityofMaryland,USA LinqiangPan,HuazhongUniversityofScienceandTechnology,Wuhan,China GheorghePa˘un,RomanianAcademy,Bucharest,Romania HendrikRichter,HTWKLeipzigUniversityofAppliedSciences,Germany JuanA.Rodriguez-Aguilar,IIIA-CSIC,Spain OttoRössler,InstituteofPhysicalandTheoreticalChemistry,Tübingen,Germany VaclavSnasel,TechnicalUniversityofOstrava,CzechRepublic IvoVondrák,TechnicalUniversityofOstrava,CzechRepublic HectorZenil,KarolinskaInstitute,Sweden AboutthisSeries The Emergence,Complexityand Computation(ECC) series publishesnew devel- opments,advancementsandselectedtopicsinthefieldsofcomplexity,computation andemergence.Theseriesfocusesonallaspectsofreality-basedcomputationap- proachesfromaninterdisciplinarypointofviewespeciallyfromappliedsciences, biology, physics, or Chemistry. It presents new ideas and interdisciplinary insight onthe mutualintersectionofsubareasofcomputation,complexityandemergence anditsimpactandlimitstoanycomputingbasedonphysicallimits(thermodynamic and quantumlimits, Bremermann’slimit, Seth Lloyd limits...) as well as algorith- mic limits (Gödel’s proof and its impact on calculation, algorithmic complexity, theChaitin’sOmeganumberandKolmogorovcomplexity,non-traditionalcalcula- tionslike Turingmachineprocessand its consequences,...)and limitationsarising inartificialintelligencefield.Thetopicsare(butnotlimitedto)membranecomput- ing,DNAcomputing,immunecomputing,quantumcomputing,swarmcomputing, analogic computing,chaos computingand computingon the edge of chaos, com- putationalaspectsofdynamicsofcomplexsystems(systemswithself-organization, multiagentsystems,cellularautomata,artificiallife,...),emergenceofcomplexsys- temsanditscomputationalaspects,andagentbasedcomputation.Themainaimof thisseries itto discussthe abovementionedtopicsfroman interdisciplinarypoint ofviewandpresentnewideascomingfrommutualintersectionofclassicalaswell asmodernmethodsofcomputation.Withinthescopeoftheseriesaremonographs, lecture notes, selected contributionsfrom specialized conferencesand workshops, special contribution from international experts. More information about this series at http://www.springer.com/series/10624 Jeff Jones From Pattern Formation to Material Computation Multi-agent Modelling of Physarum Polycephalum ABC JeffJones UnconventionalComputingCentre UniversityoftheWestofEngland Bristol UnitedKingdom ISSN2194-7287 ISSN2194-7295 (electronic) Emergence,ComplexityandComputation ISBN978-3-319-16822-7 ISBN978-3-319-16823-4 (eBook) DOI10.1007/978-3-319-16823-4 LibraryofCongressControlNumber:2015937729 SpringerChamHeidelbergNewYorkDordrechtLondon (cid:2)c SpringerInternationalPublishingSwitzerland2015 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor theeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinorforany errorsoromissionsthatmayhavebeenmade. Printedonacid-freepaper SpringerInternationalPublishingAGSwitzerlandispartofSpringerScience+BusinessMedia (www.springer.com) For Wendy Preface This book describes simple multi-agent mechanisms which model the be- haviour of an extraordinary creature, the true slime mould Physarum Poly- cephalum. This giant (up to square metre sized) single-celled organism was onceknownonlyforitscuriousbiologicalpropertiesandbehaviour.Sincethe start of this 21st Century, however, it has been the subject of a wide range of studies into its computational abilities. Physarum is both fascinating and puzzling because it can perform such complex biological and computational feats without a brain, or indeed any specialised nervous tissue. It has since becomethesubjectofintensiveresearchinbothclassicalandunconventional computing and robotics research. To model the behaviour of slime mould in this book, we describe and ex- plorethe complexpatternformationthatemergesfrominteractionswithina populationofverysimplemobileagents.Theagentsthemselvesaresosimple and generic that they may be regarded as particles, yet their interactions yield surprisingly complex emergent patterns. An evaluation of the pattern formationproducedbytheseparticleinteractionsisdescribed,alongwiththe effectsofkeymodelparameters.Weshowthatthesepatternsexhibitsecond- order behaviours which approximate phenomena observed in physical sys- tems, including self-organised network assembly and network minimisation. We use these emergent and quasi-physical pattern formation mechanisms as the basis of a simple bottom-up model of Physarum slime mould. We re- produce its biological behaviour, demonstrating how Physarum may offload somecomputationtotheenvironmentinaparsimonioustwo-waymechanism of sensing — and subsequently modifying — spatial diffusion gradients. Wethenshowhowthisvirtualslimemould(aswithrealslimemould)canbe consideredasamaterial-based,spatiallyrepresented,unconventionalcomput- ing substrate, approximatinga wide range of computing problems by propa- gationthroughspaceandmorphologicaladaptation;includingpathplanning, proximitygraphformationandminimisation,convexhulls,concavehulls,in- ternalskeletons,Voronoidiagrams,combinatorialoptimisation(bothfeedback VIII Preface controlledandsimple‘blind’methods),datasmoothing,splinecurves,simple geometricandnumericalstatisticalanalysis,andnoisyestimation. Themodelcanalsoreproducethespontaneousandself-organisedemergence ofoscillationswithin the ‘material’ofwhichit is composed.We demonstrate howtheemergenceandsynchronisationofoscillationswithintheplasmodium canalsooccurinthemodel,replicatingthetypicaloscillationpatternsofthe Physarum plasmodium.We subsequentlydemonstratehowthese oscillations canbeharnessedtogeneratedistributedcollectivetransportmechanismsand controllablesoft-bodiedamoeboidmovement. Weconcludebyconsideringhowthemulti-agentapproachcanbeextended beyond modelling Physarum into the realm of modelling other dynamical systemsincluding repulsiveparticles,mixedmaterialtypes,phaseseparation phenomena, patterning in growing materials, phyllotaxis-type patterns and 3D transport networks. The results in this book demonstrate the power and range of harness- ing emergentphenomena arisingin simple multi-agentsystems for biological modelling, computation and soft-robotics applications. With the aid of rich explanatory images, video recordings and interactive simulations the reader canexplorethepowerofbottom-upmulti-agentmodelsandwillhopefullybe motivated to explore and develop their own experiments with these simple yet powerful systems. November 2014 Jeff Jones Bristol Acknowledgements I would like to thank: • Andrew Adamatzky for his experimental ‘wet’ slime mould contributions to Chapters 9, 10, 12 and 13. And also for his designs of composite logic gates that were implemented in Chapter 7. But most importantly for his relentlesssupport,insights,motivationandencouragement.Afinermentor could not be had. • Soichiro Tsuda for his help and experimental contribution to Physarum oscillatory synchronisation in Chapter 15. • Larry Bull for his advice and positive support. • Anumberofpeoplewhohavehelpedmeininformal,butconstructiveand motivational,support,includingBenDeLacyCostello,SusanStepneyand Yukio-Pegio Gunji. • ThomasDitzinger,EngineeringEditorial,Springer-Verlag,forhis support and help. • Mr.GSenthilkumar,ECCProcessingTeam,ScientificPublishingServices, for his proofing assistance. I am grateful for the funding support of the University of the West of England Department of Computer Science and the award of a UWE SPUR Early Career Research grant, the award of Leverhulme Trust Research Fellow, and the funding provided by the EU research programme FP7 ICT Ref 316366. Contents Part I Slime Mould Physarum Polycephalum 1 Introduction and Overview............................ 3 1.1 Introduction and Overview ............................ 3 1.2 Objectives........................................... 4 1.3 Methodology......................................... 4 1.4 Structure of the Book................................. 5 2 Slime Mould Physarum Polycephalum ................. 13 2.1 Introduction ......................................... 13 2.2 Physarum Polycephalum............................... 13 2.3 Generation of Contractile Force and Oscillation Rhythm... 15 2.4 Formation and Adaptation of the Plasmodial Tube Network........................................ 16 2.5 Oscillatory Synchronisation within the Plasmodium....... 17 2.6 Computational Behaviour of Physarum Polycephalum ..... 19 2.7 Physarum Polycephalum and Robotics .................. 23 2.8 Computational Models of Physarum Polycephalum ....... 25 2.9 Physarum as a Dynamical LALI Mechanism of Pattern Formation ........................................... 27 2.10 Requisite Properties for Physarum Polycephalum Models.............................................. 28 Part II Modelling Physarum Polycephalum 3 A Multi-agent Model of Physarum .................... 33 3.1 Introduction ......................................... 33 3.2 Motivations for Model Choice .......................... 33 3.3 A Multi-agent Virtual Material Approach ............... 35 3.4 Growth and Adaptation of the Virtual Plasmodium....... 40
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