working with complex adaptive systems presentation to the good practice in action seminar
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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
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