WORKING WITH WORKING WITH COMPLEX ADAPTIVE SYSTEMSCOMPLEX ADAPTIVE SYSTEMS

Presentation to thePresentation to theGood Practice in Action SeminarGood Practice in Action Seminar

What we’ll coverWhat we’ll coverThe Defence Review 09Modelling and simulation - why they

matter to DefenceModelling and simulation - why they are

proving useful for social policyIntervention logic – what is it?Intervention logic – why is it important?Some ethical issues

What we’ll coverWhat we’ll cover

Different dimensions of the problem of developing a robust intervention logic

Static v dynamicSimple v complexNon-adaptive v adaptivePredictable v chaotic v stochasticThe role of information

What we’ll coverWhat we’ll coverInformation theory and cyborg sciencesGame theorySystem theory and system simulationNetworks and social network analysisCellular automataComplex adaptive systemsEntity-based simulationAgent-based simulation

The Defence Review 09The Defence Review 09A periodic major review required by the

Defence Act 1990Looks out to 2035Examines the present and future

geopolitical and strategic environmentIdentifies credible defence and security

risksRecommends the military capabilities

needed by NZ

The Defence Review 09The Defence Review 09Significant management issuesOrganisational structureManagement of human resourcesManagement of procurementManagement of the Defence estateFinancial managementLong-term funding track

Modelling and simulationModelling and simulationWhy they matter to DefenceWhy they matter to Defence

Military engagements are generally life-and-death – no “do-overs”

Geopolitical and strategic assessments are extremely complex

Capability must be made, not boughtNew types of warfare - network centric,

3-block, 4th generationPeace support operations

Modelling and simulationModelling and simulationWhy they are proving usefulWhy they are proving useful

for social policyfor social policy

Help overcome the limitations of previous approaches

Help overcome the limitations of human information processing

Enable policy proposals to be tested before being implemented

Help identify unexpected or “emergent” phenomena

Help assess the likely impacts of adaptation

Intervention logic – what is it?Intervention logic – what is it?

An intervention logic is a formal statement that expresses why the proposed actions are expected to result in particular outcomes

Simple Example: Drug dependence is a cause of crime. Reducing the incidence of drug dependence will reduce the incidence of criminal offending.

Intervention logic – what is it?Intervention logic – what is it?

Intervention logic is based on some thought model of how the “world” works

Can be expressed as a chain of formal (modal) logic

Interventions are an exercise in controlIf the thought model is wrong, the

intervention will not produce the desired outcomes

Intervention LogicIntervention LogicWhat it isn’tWhat it isn’t

Agency produces outputs and provides services

Then a miracle happens!Then the desired outcome is achieved

Intervention LogicIntervention Logic

Need to understand the kind of causal structure being analysed

Static v dynamicSimple v complexNon-adaptive v adaptivePredictable v chaotic v stochastic

Intervention LogicIntervention Logic

The causal structure influences the nature of the models that should be used: - for example

Non-adaptive and deterministic – control theory

Simple and adaptive – game theoryDeterministic and chaotic – chaos theorySimple and stochastic – risk theoryComplex and adaptive – complexity

theory, CAS, agent-based simulation

Some Ethical IssuesSome Ethical IssuesOutcomes matter to clientsHipprocrates admonition – First do no

harm!Unethical to intervene without doing as

much as possible to “product test”Unethical to expend valuable resources

in pursuit of an unknowable benefit

The Role of InformationThe Role of InformationDefined in the context of uncertaintyMeasured by the extent to which

uncertainty is reducedProvides a basis for drawing inferencesProvides a basis for comparing

alternative modelsNo analytical method can substitute for

insufficient information

Information TheoryInformation TheorySeminal work of Claude ShannonNow used in very many disciplinesSome social sciences now draw heavily

on concepts – the cyborg sciencesGood text – Information Theory,

Inference and learning Algorithms (David Mackay)

Game TheoryGame TheorySeminal work of John Von NeumannUseful tool for examining contested

situationsUseful tool for examining the

emergence of cooperation and alliancesLandscape theory – Robert AxlerodGood text – Games and Information

(Eric Rassmussen)

Systems TheorySystems TheoryNumerous originsSeminal work of Ludwig Von Bertalanffy

(general systems theory)Hard and soft systems theorySystems dynamics – seminal work of

Jay ForresterSystem dynamic modellingGood text – Systems Thinking and

Systems Modelling (Kambiz Maani and Robert Cavana)

Network TheoryNetwork Theoryand Social Network Analysisand Social Network Analysis

Much studied in operations researchNetworks are critical infrastructureDifferent levels of robustness – e.g. star

v distributedSocial network analysis examines

interrelationships between peopleImplications for community agencies

and social policyGood text – The Development of Social

Network Theory (Linton Freeman)

Prediction and ChaosPrediction and Chaos Can’t control what you can’t predict Deterministic situations are usually most

predictable Deterministic situations may still be hard to

predict – the weather Characteristic of chaos – sensitive to initial

conditions Chaotic trajectories may have strange

attractors – Edward Lorentz “Adaptive” situations can be very hard or

impossible to predict

Cellular AutomataCellular AutomataA way of examining the collective

behaviour of cellular “agents”Origin in “game of life” – John Horton

ConwaySimulation usually uses a computerVery good way of illustrating basics of

CASGood text – A New Kind of Science

(Stephen Wolfram)

Complex Adaptive SystemsComplex Adaptive SystemsSeminal work of John Holland, Murray Gell-

Mann – Santa Fe InstituteComplex in that they have multiple,

disparate, interconnected elementsAdaptive in that they can change and learn

from experienceSelf-organisingIrreversible history, unpredictable future,

emergent phenomena

Discrete-Event SimulationDiscrete-Event Simulation Models change at particular time

points triggered by one or more events No assumption that every time point

has a linked event Examples of such events are receipt of

applications for assistance and processing of such application

Good software available - ARENA

Agent-Based SimulationAgent-Based SimulationAllow interactions to occur between the

same types of entities within the systemInteractions may occur on the basis of

both space and time relationshipsRequire a good deal of accurate

information Need to be carefully verifiedSome software availableCan be very useful models

Important MessagesImportant MessagesStrong ethical imperative to have sound

intervention logicThought model must match the real

situationNumerous theoretical and software

tools now availableMust have enough information for

modellingCould your organisation defend the

logic of its interventions?

Questions?

SimulationSimulationYou get to be the “agents”Simulation run in repeated “steps”Objective is to survive possible

elimination at each stepDetermined by the outcome of

negotiation between pairsWill end up with $1, $2 or $3 after

negotiationNeed to work out the elimination pattern

SimulationSimulationInner circle and outer circleMay be moved between and within

circlesInner circle starts with $4Pairs must agree a split or be eliminatedOne immunityMay share information or deductionsMay misdirectLast one standing wins

Learning ObjectivesLearning ObjectivesHard to understand and forecast

complex adaptive systems – even when the behaviour rules are simple

Maybe provide some “humiliation therapy” for those who may think they can easily forecast social interventions