Emergent a syst em C-kur s, 5 pong, HT-04 J onny Pet t ersson j - PDF document

Emergent a syst em C-kur s, 5 poäng, HT-04 J onny Pet t ersson j onny@cs.umu.se 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 1 Cource Descript ion ❒ The f ocus of t he cource includes t he acquisit ion of : ❍ knowledge about t he concept s emergence, emergent behavior and emergent syst ems; ❍ knowledge about how agent based t echniques can be used as t ools f or modelling and simulat ion; and ❍ knowledge of what applicat ions of emergent syst ems can be used f or and how t o evaluat e t hem. 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 2 Cource Descript ion (cont .) ❒ Moment 1, t eoridel, 3 poäng ❍ Målet med kur sen är at t ge en f örst åelse f ör emergent a syst em. Emer gent a syst em är syst em där syst emet s bet eende uppst år som en emergent egenskap ur int erakt ionen mellan syst emet s delar. Emergent a egenskaper kan obser veras i alla icke-linj ära syst em som är t illr äckligt komplexa, både nat urliga och ar t if iciella. Under kur sen kommer bland annat f r akt aler , kaos, komplexa syst em och adapt at ion at t behandlas. Kur sen ut gör en gr und f ör kursen Design av samverkande syst em. ❒ Moment 2, laborat ionsdel, 2 poäng ❍ Obligat oriska uppgif t er 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 3 1

This Cource ❒ Text book + paper s ❍ Comput er programs ❒ Focus on ❍ Fract als ❍ Chaos ❍ Complex Syst ems ❍ Adapt at ion ❒ Cont ent s ❍ Lect ures ❍ Guest lect ures ❍ Assignment s ❍ Proj ect 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 4 Assignment s and Proj ect ❒ Net Logo and t ermit es ❍ Fir st (?) cont act wit h Net Logo ❍ Termit es – a simple syst em wit h emer gent behavior ❒ Ant Algorit hms ❒ Genet ic Algorit hms ❒ 2 and 2 in t he assignment s ❒ Proj ect ❍ 1 t o 4 in t he proj ect 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 5 Teaching ❒ Pedagogical t hought s ❒ Slides ❍ Sour ce ❍ Cont ent s ❍ Language ❒ What should you learn? 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 6 2

The rest of t oday ❒ Concept s ❍ Emergence, emer gent syst ems, … ❒ Lif e ❍ Real lif e ❍ Ar t if icial lif e ❒ Topics 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 7 Emergence ❒ Def init ions ❍ The whole is more t hen a sum of part s ❍ The global behavior could not be pr edict ed f rom lower levels ❍ Somet hing t hat emer ges in t he int er act ions bet ween simple(?) part s and t he environment , and t hat is not descr ibed in t he par t s ❒ Emergent propert ies ❒ Emergent syst ems ❒ Example: Ant s 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 8 Emergent Behavior ❒ Bot t om-up ❒ Dist ribut ed ❒ Local det erminat ion of behvior ❒ On all levels ❒ Example: The human body 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 9 3

Propert ies of Emer gent Syst ems ❒ Many int eract ing part s ❒ Decent ralised ❒ Non-linear ❒ Dynamic ❒ Compet it ion and cooperat ion ❒ Emergent propert ies 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 10 Many int eract ing part s ❒ Societ ies made of many people, people made of many or gans, organs made of many cells ❒ A syst em of par t s because of int eract ions ❒ Number of part s may dif f er ❒ Massive parallelism ❍ Of t en many simple part s doing t he same t hing ❍ Complexit y comes f r om int eract ion ❒ Example: Weat her 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 11 Decent ralised ❒ Self -organisat ion ❍ The order emer ges f rom t he syst em it self ❒ Advant ages of decent ralisat ion ❍ Easier t o adapt t o changes ❍ A syst em does not need t o have a smar t leader ❒ Examples: ❍ WWW ❍ Peer-t o-peer archit ect ural models 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 12 4

Non-linear ❒ Do not obey t he superposit ion principle ❍ Out put is not propor t ional t o input ❒ I nt eract ions bet ween part s ❒ Example: Phase t ransit ions ❍ Solid – liquid - gas 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 13 Dynamic ❒ Of t en t he int er act ions cont inues on and on ❍ Does not always come t o a ”f ixed” st at e ❍ Can be bet t er t o handle changing environment s ❒ Dynamic syst ems can have dif f er ent amount s of complexit y ❒ Example: Societ y 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 14 Compet it ion and Cooperat ion ❒ Some agent s may cooperat e ❒ Some agent s may f ight f or t he same resource ❒ Some agent s may dest r oy what ot hers t ries t o do ❒ Example: Producer-consumer syst ems 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 15 5

Discussion ❒ Quest ions t o consider: ❍ What is t he emergent pr oper t y? ❍ What is t he goal of t he syst em? ❍ Does each agent know t he goal? ❍ How was t he syst em cr eat ed? ❒ Emergent syst ems in t he socit y ❒ Emergent syst ems in t he nat ure 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 16 Complex Syst ems ❒ (Almost ) like emergent syst ems ❍ Many part s ❍ I nt er dependent par t s ❒ Dif f icult t o under st and ❍ The behavior of t he whole syst em underst ood f rom behvior of t he par t s ❍ The behavior of t he par t s depends of t he behavior of t he whole syst em ❒ Example: Family 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 17 Adapt at ion ❒ Can lead t o improved f it ness and perf or mance, or j ust t o be able t o survive ❒ Adapt at ion can happen in t hr ee ways ❍ I mproved handling of an event by t he agent ❍ Learning – in t he lif et ime of t he agent ❍ Evolut ion – acr oss generat ions 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 18 6

Complex Adapt ive Syst ems ❒ An complex adapt ive syst em is a syst em consist ing of many int eract ing part s. The behavior of t he syst em emer ges out of t he parallel int eract ions bet ween t he part s and t he environment wit hout any global plan. The part s adapt and evolve over t ime. ❒ Example: Ecosyst ems 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 19 Lif e – What is Lif e? ❒ Vit alism ❍ Lif e is ”somet hing” ext ra over and above t he det ailed organizat ion of a mat erial organism ❒ Langt on, 1988 ❍ ”… living organisms are not hing more t han complex biochemical machines. … A living organism … must be viewed as a large populat ion of relat ively simple machines.” ❍ ”Lif e is a propert y of f orm, not mat t er” ❒ Flake, 1998 ❍ ”Nat ure appears t o be a hierarchy of comput at ional syst ems t hat are f orever on t he edge bet ween comput abilit y and incomput abilit y.” 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 20 Lif e - Biology ❒ The Concise Oxf or d Dict ionary, 1990 ❍ Biology – The st udy of living or ganisms ❒ Mer riam-Webst er ´ s Collegiat e Dict ionary ❍ Biology - A branch of knowledge t hat deals wit h living or ganisms and vit al processes ❒ From greek ❍ bios – lif e ❍ logus - discour se ❒ Does it have t o be t he st udy of coal-based lif e? 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 21 7

Lif e – Art if icial Lif e ❒ Langt on, 1988 ❍ ”Art if icial Lif e is t he st udy of man-made syst ems t hat exhibit behaviors char act er ist ic of nat ur al living syst ems.” ❍ ”… Ar t if icial Lif e can cont r ibut e t o t heor et ical biology by locat ing lif e-as-we-know-it wit hin t he larger pict ure of lif e-as-it -could-be .” ❍ ”The ar t if icial in Ar t if icial Lif e r ef er s t o t he component par t s, not t he emer gent pr ocesses.” 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 22 From Chaos t o Lif e ❒ Living organisms are nonlinear syst ems! ❒ Living or ganisms are complex syst ems! ❒ How has nat ure achieved t his? 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 23 From Chaos t o Lif e - Nat urally ❒ Evolut ion t hrough nat ural select ion ❍ Darwin, The Origin of Species , November 24, 1859 ❍ Genot ype – phenot ype ❍ Cr it er ia f or evolut ion • Heredit y • Variabilit y • Fecundit y ❒ Co-evolut ion ❍ A necessar y condit ion? ❒ Self -similarit y ❒ Self -organizat ion 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 24 8

From Chaos t o Lif e - Art if icially ❒ How t o do t his art if icially? ❍ Can not pr edict t he global behavior of simple int eract ing subpar t s ❍ Can not decide which subpar t s t o use t o get a predet ermined global behavior ❒ You must ”run” t he syst em t o see what kind of global behavior it generat e ❒ You need met hods t o search t hrough t he solut ion space of a nonlinear syst em 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 25 From Chaos t o Lif e - Art if icially ❒ Met hods in Art if icial Lif e ❍ Lindenmayer syst ems ❍ Cellular Aut omat a ❍ Boids, her ds and f locks ❍ Ant Algor it hms ❍ Genet ic Algor it hms ❍ And mor e… 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 26 Fract als ❒ Lindenmayer syst ems ❍ Consist of set s of r ules f or r ewr it ing st r ings of symbols ❍ “Random pr ocesses in nat ur e ar e of t en self - similar on var ying t empor al and spat ial scales” (Flake, 1998) ❍ Example: Flake 2/11 - 04 Emergent Systems, Jonny Pettersson, UmU 27 9