WORKING WITH COMPLEX ADAPTIVE SYSTEMS Presentation to the Good Practice in Action Seminar

What well cover The Defence Review 09 Modelling and simulation - why they matter to Defence Modelling and simulation - why they are proving useful for social policy Intervention logic – what is it? Intervention logic – why is it important? Some ethical issues

What well cover Different dimensions of the problem of developing a robust intervention logic Static v dynamic Simple v complex Non-adaptive v adaptive Predictable v chaotic v stochastic The role of information

What well cover Information theory and cyborg sciences Game theory System theory and system simulation Networks and social network analysis Cellular automata Complex adaptive systems Entity-based simulation Agent-based simulation

The Defence Review 09 A periodic major review required by the Defence Act 1990 Looks out to 2035 Examines the present and future geopolitical and strategic environment Identifies credible defence and security risks Recommends the military capabilities needed by NZ

The Defence Review 09 Significant management issues Organisational structure Management of human resources Management of procurement Management of the Defence estate Financial management Long-term funding track

Modelling and simulation Why 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 bought New types of warfare - network centric, 3-block, 4 th generation Peace support operations

Modelling and simulation Why they are proving useful for 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? 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 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 control If the thought model is wrong, the intervention will not produce the desired outcomes

Intervention Logic What it isnt Agency produces outputs and provides services Then a miracle happens! Then the desired outcome is achieved

Intervention Logic Need to understand the kind of causal structure being analysed Static v dynamic Simple v complex Non-adaptive v adaptive Predictable v chaotic v stochastic

Intervention 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 theory Deterministic and chaotic – chaos theory Simple and stochastic – risk theory Complex and adaptive – complexity theory, CAS, agent-based simulation

Some Ethical Issues Outcomes matter to clients Hipprocrates 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 Information Defined in the context of uncertainty Measured by the extent to which uncertainty is reduced Provides a basis for drawing inferences Provides a basis for comparing alternative models No analytical method can substitute for insufficient information

Information Theory Seminal work of Claude Shannon Now used in very many disciplines Some social sciences now draw heavily on concepts – the cyborg sciences Good text – Information Theory, Inference and learning Algorithms (David Mackay)

Game Theory Seminal work of John Von Neumann Useful tool for examining contested situations Useful tool for examining the emergence of cooperation and alliances Landscape theory – Robert Axlerod Good text – Games and Information (Eric Rassmussen)

Systems Theory Numerous origins Seminal work of Ludwig Von Bertalanffy (general systems theory) Hard and soft systems theory Systems dynamics – seminal work of Jay Forrester System dynamic modelling Good text – Systems Thinking and Systems Modelling (Kambiz Maani and Robert Cavana)

Network Theory and Social Network Analysis Much studied in operations research Networks are critical infrastructure Different levels of robustness – e.g. star v distributed Social network analysis examines interrelationships between people Implications for community agencies and social policy Good text – The Development of Social Network Theory (Linton Freeman)

Prediction and Chaos Cant control what you cant 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 Automata A way of examining the collective behaviour of cellular agents Origin in game of life – John Horton Conway Simulation usually uses a computer Very good way of illustrating basics of CAS Good text – A New Kind of Science (Stephen Wolfram)

Complex Adaptive Systems Seminal work of John Holland, Murray Gell- Mann – Santa Fe Institute Complex in that they have multiple, disparate, interconnected elements Adaptive in that they can change and learn from experience Self-organising Irreversible history, unpredictable future, emergent phenomena

Discrete-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 Simulation Allow interactions to occur between the same types of entities within the system Interactions may occur on the basis of both space and time relationships Require a good deal of accurate information Need to be carefully verified Some software available Can be very useful models

Important Messages Strong ethical imperative to have sound intervention logic Thought model must match the real situation Numerous theoretical and software tools now available Must have enough information for modelling Could your organisation defend the logic of its interventions?

Questions?

Simulation You get to be the agents Simulation run in repeated steps Objective is to survive possible elimination at each step Determined by the outcome of negotiation between pairs Will end up with $1, $2 or $3 after negotiation Need to work out the elimination pattern

Simulation Inner circle and outer circle May be moved between and within circles Inner circle starts with $4 Pairs must agree a split or be eliminated One immunity May share information or deductions May misdirect Last one standing wins

Learning Objectives Hard 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