Paris, FRANCE25-27 Nov 2009

International Collaborative Research Program International Collaborative Research Program Causality in Complex SystemsCausality in Complex Systems

Can we use “Attractors” as a way to reduce the dimensionality of the

phase space of C&INs?

RationaleRationale

How do experts make sense of complex phenomena in their domains?

higher-level conceptual structures reduce dimensionality of searches

So what are the relevant higher-level concepts for C&INs?

We know interactions and dynamics are more important than composition and static configurations

The main sources of dynamically organised complexity are adaptive, self-organising and regulatory processes

Maybe these should be the building blocks of a higher-level conceptual map of the system?

how do they interact?

What are the recurring and/or persistent patterns and structures (attractors and repellors? What else?) that they can create?

Can we develop a “physics of interacting adaptive and S-O processes”?????

What is known about Interacting What is known about Interacting Adaptive (and S-O) Processes?Adaptive (and S-O) Processes?

Population dynamics study co-evolution of species Arms races and the Red Queen effect Rehabilitation of group selection (DS Wilson, Okasha, and others)

Hot topic in theoretical biology: multi-level selection theories (-> one million hits in google)

Niche Construction – explicitly addressing interaction between genetic evolution and adaptive processes that shape the environment inherited by progeny counterintuitive and very significant effects on outcomes (Odling-Smee, Laland, Feldman)

Interactions between different inheritance systems (Genetics, Epigenetics, Behavioural, Symbolic) (Jablonska and Lamb, )

Our own conceptual framework for adaptation Five levels of adaptation of which 4 involve applying adaptation to adaptive processes

Evo-devo studies address interaction between evolutionarily developed S-O processes and clade selection processes (Kirschner and Gerhart)

… lots more

But can we develop a general theory???

Some ways of thinking about it …Some ways of thinking about it …

Bottom-Up: Pick a real C&IN or a ‘toy’ version of one and try to explore its

dynamics using these approaches

Top-down: Start with generic model of adaptation

[variation, interaction, feedback, fitness-linked selection] operating on a system possessing [sense, ‘decide’, act] functions in a context

classify possible interaction pathways between two generic instances

Do this in a time-explicit way Generalise to multiple interacting instances What are the possible robust emergent patterns? What are the possible transient phenomena that can significantly

alter the dynamic development of the situation?

An attempt at the Bottom-up approachAn attempt at the Bottom-up approach

Real Problem: How can we better understand the complex situation in the Afghanistan – Pakistan region and come up with more effective strategies for improving the situation?

Toy Problem: How can we better understand the intractability of the IED problem in a particular province and come up with more effective strategies for significantly reducing them?

Relevant CAS conceptsRelevant CAS concepts

Robustness

Adaptationapplies to:• ourselves (how we learn, develop strategy, plan and execute, improve capabilities, foster cooperation …)• adversaries (how they learn and change, how they decide what to do) • target populations (how they learn and change, how they decide what to do)• others ….

tipping points

thresholds

Self-organisationHow patterns of interaction emergent patterns

transformability

“attractors” ?

Multiscalarityapplies to:• agents• intents• attractors• timescales• decisions• actions

Intractability

Resilience

Multiscale Intent Framework Multiscale Intent Framework depends on understanding of contextdepends on understanding of context

How frequently changed

What actor wants or intends to achieve

(ends --- means)

Actor’s concept of how to achieve

Intention (ways)

dependence on actor’s

understanding of context

needed contextual appreciation:

scope | resolution

core values none not applicable

Success / Failure high very wide low

Stratagem very high very wide low

proxies for success/failure very high wide medium

course of action high restricted high

objectives high restricted high

plan medium narrow higher

tasks low specific aspects very high

procedures low local very high

Enduring

? as

understanding develops

? as situation

develops

? moment by

moment next step low local very high

Adaptation Adaptation = “engines of change” in human systems= “engines of change” in human systems

Through adaptation a complex adaptive system changes over time in a way which tends to increase its ‘success’

Being adaptive requires:

1. Concept of ‘success or failure’, or ‘fitness’, for the system in its context

2. A source of variation in some internal details of the system, and

3. A fitness-linked selection process, i.e. the system preferentially retains/discards variations which enhance/decrease its fitness, which requires…

4. A way of evaluating impact of a variation on fitness – through feedback from interaction with its context (or from running an internal model).

Adaptation amounts to betting on the future being somewhat like the past.

Adaptation is a major process whereby complex adaptive systems such as living organisms, and organised groups change their characteristics and behaviours

We need to understand and harness it in many ways IOT influence the development of human systems

Detailed conceptual models and frameworks exist (refs available)

variationvariation

interactioninteraction

feedbackfeedback

success-linked success-linked selectionselection

HypothesesHypotheses• Adaptive responses of agents can interact in synergistic or antagonistic ways• Synergistic networks of adaptive responses can create robust and persistent

features - ‘attractors’ - of complex situations • An event or development that might perturb the ‘attractor’ stimulates adaptive

responses from agents most directly affected, which then stimulate several waves of further adaptive responses from other agents through their interactions.

• Net effect of all the adaptive responses is to return the situation to the ‘attractor’ region and stabilise it

• Use of IEDs, corruption in public officials, cultivation of opium, are examples of such ‘attractors’ in the possibility space of PAKAF

• Organised crime and drug use in big cities are other examples• Many ‘attractors’ at one scale interact to create larger scale ‘attractors’ eg IEDs,

corruption, poppy cultivation and other robust features in PAKAF interact to create an intractable situation (one cant be solved without solving the others)

• It is useful to develop understanding of the network of adaptive responses IOT identify potentially effective interventions

• It is important to also understand the potential of the situation for being in different ‘attractors’

– to design intervention strategies to bring about more desirable ‘attractors’ at the relevant scales– AND to be aware of other potentially dangerous ‘attractors’ to be avoided.

• Disciplined application of a methodology (yet-to-be-developed) based on these hypotheses would produce a strategy and accompanying framework of measures to be monitored that would give insight into where the situation is in its ‘attractor space’ and how it is tracking, providing the necessary feedback for adaptive implementation and refinement of the strategy

First steps to application to ‘toy’ scenarioFirst steps to application to ‘toy’ scenario - motivating factors - motivating factors

Ideologically driven

pragmatically driven

groupsindividuals IEDS

$$

intimidation

Better optionsto pursuegoals

Nonradicaleducation

Better waysto pursue ideals

Strategic effect

Against principles

Inspire, support, teach

CoerceReward

TrainThreaten

• Who are the relevant agents? - individuals & groups; - specific & classes

• What are their intent frameworks?

• How do all the other agents respond to one changing their posture?

• how do those responses trigger other responses and what is net effect?

• how can we represent these networks of interacting adaptive responses ?

LeadWork for

Powerstruggles

LeadWork for

Radicaleducation

Socialpressure

Better optionsto achievepower

excitement anger

Linked toothers that benefit

recognitionstatus

First steps to application to ‘toy’ scenario First steps to application to ‘toy’ scenario - actions- actions

Ideologically driven

pragmatically driven

groupsindividuals IEDS

Engage in legitimate political and economic actionInspire,

support, teach

CoerceReward

TrainThreaten

LeadWork for

LeadWork for

Seek to influence other groups & individuals away from violence

Incite violence, publicise and praise violent acts, demonise opponents

INCOMPLETE

Insights from relevant scientific domainsInsights from relevant scientific domains

Examples of transformations of attractors:

Regime shifts in ecosystems

Interventions that change entrenched metacognitive behaviours

Stem cell research on switching cell fates

Phase changes in physical systems

Work on understanding resilience

Robust-Yet-Fragile systems

Cascading failures

What Next and Where to? What Next and Where to?

How to discover potential attractors that the situation is

not currently in?

How to visualise?

What other structures might there be?

Regions of greater influencability (eg between two

potential attractors?)

???