Knowledge Management

Complexity theory and

Walter Baets, PhD, HDRAssociate Dean for ResearchAssociate Dean for ResearchMBA DirectorProfessor Complexity , Knowledge and InnovatioEuromed Marseille – Ecole de Management

Erna Baets Oldenboom, MA, MPhilProfessor Leadership, Sustainable Performance,

t and Management Learning

the quantum interpretation

on

and Mind/Body Medicine

Flatland: Edwin Abbo

A. Square meetq

tt, 1884

ts the third dimension

Sometimes small differe

conditions generate very

in the final phenomena.

former could produce a

the latter.

Prediction becomes impo

accidental phenomena.

PP

ences in the initial

y large differences

A slight error in the

tremendous error in

ossible; we have

i é i 1903oincaré in 1903

Sensitivity to initial

X * XXn+1 = a * Xn

0.294 1.4 0.3

conditions (Lorenz)

* (1 X )n * (1 - Xn)

3 0.7

Cobweb Diagrams (AttCobweb Diagrams (Att

Xn+1 = μ * Xn *

dX / dt = μ X (1 -μ (

On the diagram• Parabolic curv

Di l li• Diagonal line • Line connectin

tractors/Period Doubling)tractors/Period Doubling)

(1 - Xn) (stepfunction)

- X) (continuous function)) ( )

ms one gets:ve

X XXn+1 = Xnng iterations

Lorenz curve (But

L (1964) fi ll bl Lorenz (1964) was finally able

Lorenz weather forecasting mo

dX / dt = B ( Y - X )

dY / dt = - XZ + rX - Y

dZ / dt = XY - bZ

tterfly effect)

t t i li P i é’ l i to materialize Poincaré’s claim

odel

Hénon Att

X n+1 = 1 - a X n+1 a

Y n+1 = b * X n+1

A in diff nt ttAgain, different attr

Other examples: PenPoincaré, HorsePoincaré, Horse

tractor

* X 2 n + Y n X n Y n

nn

t h nractors are shown

ndulum of e Shoee Shoe

h h Why can chaos n

• Social systems areSocial systems arenon-linear

• Measurement can Measurement can

M i l• Management is alwapproximation oapproximation ophenomenon

b d d not be avoided ?

e always dynamic and e always dynamic and

never be correctnever be correct

di i ways a discontinuous of a continuous of a continuous

Ilya Prigogine

• Non-linear dynamic mperiod doublingperiod doubling,….

• Irreversibility of tim• Irreversibility of tim

• The constructive roleThe constructive role

• Behavior far away froBehavior far away fro

• A complex system = cA complex system = c

• Knowledge is built froKnowledge is built frobottom up

models (initial state, ).)

me principleme principle

e of timee of time

om equilibrium (entropy)om equilibrium (entropy)

chaos + orderchaos + order

om the om the

Entropy

M sur f r th m unt f dMeasure for the amount of d

When entropy is 0, no furtheWhen entropy is 0, no furthe(interpretation is that no info

h There is a maximum entropy diagram, this is 4)

Connection between statisticaentropy to a chaotic system py yassociated statistical system

dis rd rdisorder

er information is necessaryer information is necessaryormation is missing

h ( h b fin each system (in the bifurcation

al mechanics and chaos is applying in order to compare with anp

Francesco VarelaFrancesco Varela

• Self-creation and selsystems and structuy

• Organization as a neu• The embodied mind• Enacted cognition• Subject-object divisj j• How do artificial netw• Morphic fields and mp

(Sheldrake)

lf-organization of ures (autopoièse)( p )ural network

ion is clearly artificialyworks operate (Holland)

morphic resonance p

Chris LangtonChris Langton

Artificial life researchArtificial life research

Genetic programming/a

Self-organization (the

Interacting (negotiatin

algorithms

bee colony)

ng) agents

Conway’s game of

One of the earlier artific

Simulates behavior of sin

Rules:

•Any live cell with fewer than •Any live cell with more than t•Any dead cell with exactly th•Any cell with two or three ne

next generationnext generation

Plife.exe (windows)( )

f life

cial life simulations

gle cells

two neighbors dies of lonelinessthree neighbors dies of crowdinghree neighbors comes to lifeeighbors lives, unchanged to the

John HollandJ H

Father of genetic progr

Agent-based systems (n

I di id ls h li it d Individuals have limited

Individuals optimize theIndividuals optimize the

Limited interaction (com

ramming

network)

h t isti s characteristics

eir goalseir goals

mmunication) rules

Law of increasing Law of increasing (Brian Arthur)

• Characteristics of th( li d(a non-linear dynam

• Phenomenon of incre

• Positive feed-back

• No equilibrium

• Quantum structure oQ m(WB)

returns returns

he information economyi )ic system)

asing returns

of business f

Summary (un

• Non - linearity• Dynamic behavio• Dynamic behavio• Dependence on iP i d d bli• Period doubling

• Existence of att• Determinism• Emergence at thEmergence at th

ntil now)

ororinitial conditions

tractors

he edge of chaoshe edge of chaos

Gödel’s theorem: 1931Gödel s theorem: 1931No absolute axiomatic syst

Relativity theory (Einstein)No absolute measurement i

Quantum mechanics: first pObservation is interpretatiObservation is interpretati

Complexity theory (Prigoginp y yEmergence, bifurcations, st

tem is possible

): first part of the 20st centuryis possible

part of the 20st centuryionion

ne): second part of 20st centuryp ytrange attractors

Once holism and complm mpwe cannot avoid a fund

PAULI comple

Syy(=occurring

From causal coherence (from cause to effect)

A-cau

exity acceptedy pdamental question

ementary physics

ynchronicityy yg–together-in-time)

Coincidence (occurring together)

usal linkshence….

A quantum i

non-lonon-losynchroyentang

nterpretation

ocality; ocality; onicity; yglement

Mechanistic verThe evolution i

Product oriented Unique distribution channelsqControlStabilityM t b bj tiManagement by objectiveProcesses are the assetsHierarchical organization Hierarchical organization Machine thinking (symbolic)Industrial era

rsus organic:gn business

The client co-createsMultiple channelspEmergent processesChange (learning) is the goalM t i h d l itManagement in change and complexityLearning is the assetHuman networksHuman networksHuman thinking (fuzzy)Knowledge era

S tSome quantumMaxwell, Planck and Bohr: intro

beauty and coherenceEinstein de Br lie and SchrödEinstein, de Broglie and Schröd

continuous wave as a bacausal descriptioncausal description

Heisenberg, Pauli, Jordan and Devent-by-event causalit

ll d f d well-defined trajectorieIn 1935, Schrödinger formulatePauli: Background physics has aPauli: Background physics has a

to a natural science whias with consciousness

Pauli accepted that physical valin the eyes of the obserf h m n ns i sn ssof human consciousness

t im storiesoduced criteria such as fertility,

din er: shared a c mmitment t a dinger: shared a commitment to a asic physical entity subject to a

Dirac: we no longer have ty and particles do not follow

b k des in a space-time backgrounded his famous ‘cat paradox’n archetypal origin and that leads n archetypal origin and that leads ich will work just as well with matter

lues, as much as archetypes, change rver. Observation is the result

ss

Some quantum sq

Polkinghorne: The implication of phenomenon of “entanglephenomenon of entangleremote activity, not simpontological in nature

Polkinghorne (1990): The greatethe more the consciousnresonate with the hologrresonate with the hologr"quantum zero point" (thin an almost resting, but g,energy field

stories (2)( )

these observations is that the ement” (non-locality) includes a real ement (non locality) includes a real ply epistemological, but in fact

r the experience of satisfaction, ess of each cell in the body will raphic information engraved in the raphic information engraved in the he lowest possible state of energy, not quite, situation) of the q , )

So, on the Copenhagen interph i l t thphysical processes are, at the

inherently indeterministic anclassical physics is dead Theclassical physics is dead. Theentanglement (or non-separabgives rise to the measuremenmakes it impossible to assign arbitrary isolated physical sywith another system in the pawith another system in the pasystems are no longer interaccharacteristic of quantum sysf q m yindication of the ‘holistic’ cha

pretation of quantum mechanics, t f d t l l l b th e most fundamental level, both

d non-local. The ontology of e heart of the problem is the e heart of the problem is the bility) of quantum states that nt problem. This entanglement independent properties to an

ystem once it has interactedast even though these two ast – even though these two cting. The non-separability stems can be seen as an maracter of such systems.

A quantum in

In the arts: Cara et MurphyIn linguistics: Dalla Chiarra egIn the physical sciences: PauIn biology: Sheldrake (morphI m di i : Ch th AIn medicine: Chopra, the Ay

regular medici

nterpretation

yet Giuntiniulihogenetic fields and resonance)

d b t l i i l i yurveda, but also increasingly in ine

The Bogdanov

Beyond the « Wall Beyond the « Wall Before “the big baThere is a fifth dim

a fourth of spf f pimaginary tim

Time-space really bTime-space really bThat singularity ha

t movement any

Singularity (2)

of Planck » ? of Planck » ?ng” ?mension, beingpace expressed in p p

mebecomes a continuumbecomes a continuumas no classical

(“ h t i ”)ymore (“what is”)

The Bogdanov

Beyond the « Wall Beyond the « Wall Before “the big baThere is a fifth dim

a fourth of spf f pimaginary tim

Time-space really bTime-space really bThat singularity ha

t movement any

Singularity (2)

of Planck » ? of Planck » ?ng” ?mension, beingpace expressed in p p

mebecomes a continuumbecomes a continuumas no classical

(“ h t i ”)ymore (“what is”)

EEntra(Institute of Heart M(Institute of Heart M

Ph si l f m tiPhysiology of emotioHow emotions influe

behavior and hThe heart is a highlThe heart is a highl

a sensory orga(nervous cente(nervous cente

That “heart brain” at k d i itakes decisionthe brain’s cer

ainmentMath; www heartmath org)Math; www.heartmath.org)

sonsence cognition, healthy complex system:y complex system

an, a heart brain er)er)allows us to learn and

i d d t fns independent fromrebral cortex

Entrainme

There is a strong iThere is a strong ibody via an el

Rythms should natuRythms should natuthat heart rh

The same happens (pendulum clo(p m

Socio-emotional intmother and cmother and c

Heart coherence

nt (2)

nteraction through thenteraction through thelectromagnetic fieldurally synchronize onurally synchronize onhythmbetween people

ocks: Huygens)yg )teraction between hildhild

A beginning of g gSome research pr

Complexity and emergent learninp y gAgents, Sara Lee/DE

Innovation in SME’s: a network sANN b i t iANNs, brainstorm sessio

Telemedecin: a systemic researcmedical care market:medical care market:Agents

Knowledge management at Akzo creation ability: ANNs, Akzo Nobel

Information ecology: Information ecology: For the moment a concepAgentsg

Conflict managementAgents

K l d t t BiKnowledge management at BisonAgents

evidenceojectsng in innovation projects:g p j

structure:onsch into the ICT innovations in the

Nobel: improving the knowledge

ptual model

t ib ti t i ti: contribution to innovation

ResearchI h f In search of «

Expected contributions

• Can we visualize synchronicit• What are the organizing prin

emergenceemergence• Emergent concepts in manag• « Complex Adaptive SystemsComplex Adaptive Systems

Agents, Neural Networ• The contribution of this par

i i i iinnovation in companies• Another understanding of inn

h agendah i itsynchronicity »

s

ty in managementnciples and what is precisely

ements » as research tools s as research tools rks, Learning systemsadigm for knowledge, learning and snovation