Exploring Complex Adaptive Systems Dr Niki Jobson, Dstl, UK Dr Anne - - PowerPoint PPT Presentation

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Exploring Complex Adaptive Systems Dr Niki Jobson, Dstl, UK Dr Anne - - PowerPoint PPT Presentation

Exploring Complex Adaptive Systems Dr Niki Jobson, Dstl, UK Dr Anne Marie Grisogono, DSTO, Australia TTCP Joint Systems and Analysis Group, AG 14 Complex operational environment From The DCDC Global Strategic Trends Programme 2007 2036 ,


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Exploring Complex Adaptive Systems

Dr Niki Jobson, Dstl, UK Dr Anne‐Marie Grisogono, DSTO, Australia TTCP Joint Systems and Analysis Group, AG 14

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Complex operational environment

Simple cause– effect models fail The ‘rules’ keep changing Actions have unintended consequences Coherent behaviour, uncertain of causes

From The DCDC Global Strategic Trends Programme 2007 – 2036, Third Edition From The Comprehensive Approach, Joint Discussion Note 4/05

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New problems require new approaches

biological sciences information sciences cognitive sciences

  • rganisational

sciences evolutionary economics physical sciences maths & computing social sciences

Complex Systems Science

Design and management principles for CAS Methodologies, guidelines, tools and techniques Understand fundamental processes in CAS Causality and influenceability in CAS

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Ansgar Walker, http://www.Wikimedia.org

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May have many kinds

  • f elements/agents,

elements can be distinguishable by functions or specialisations Elements can interact in relatively simple ways (linear & non-linear) Open system: exist in, & interact with a context: exchange information, energy, materials Patterns interact higher

  • rder patterns

Coherent dynamic behaviours dynamic patterns emerge Leading to seemingly chaotic behaviour Interdependent propagation of effects small changes in initial parameters can have “large” effects Hierarchical or nested multi-scale structure Systems

Complex Systems

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Complex Adaptive Systems

  • Additional property of adaptivity:
  • structure and behaviour of the system changes over time in a

way which tends to increase its ‘success’ or ability to thrive

  • Natural living systems, ‘engineered’ systems and socio‐

technical systems

Systems

Complex Systems

CAS

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Emergence, scope and scale (1)

From http://www.commons.wikimedia.org

Emergence is coupled to scope Emergence is coupled to scope …. and scale …. and scale

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Emergence, scope and scale (2)

  • Studying either macrostate or microstate in isolation is

not adequate

  • Requires a multi‐scale approach
  • Need to establish which aspects of the microstate are relevant to

the key emergent properties/behaviours at macrostate

  • Iterative analysis, combine top down and bottom up
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Complexity and scale

Based on Bar-Yam Y., Complexity of Military Conflict: Multi-scale Complex Systems Analysis of Littoral Warfare, NECSI, 2003

System Complexity

(no. poss independent behaviours)

Scale of behaviour

Fine scale Coarse scale

When the independence of the parts is reduced, the scale of behaviour is increased When the independence of the parts is reduced, the scale of behaviour is increased Coherent agents Coordinated agents Independent agents

http://www.FreeFoto.com

Trade off between large scale behaviour and fine scale complexity Trade off between large scale behaviour and fine scale complexity

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Complexity and scale in organisations (1)

  • Different mission have different requirements
  • Vary in complexity and scale
  • Successful force:
  • Able to achieve many tasks across the range of scales through

matching its organisational complexity to the task

  • Making appropriate trade‐offs between complexity and scale

System Complexity Scale of behaviour

Fine scale Coarse scale

Coalition forces Insurgents

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Complexity and scale in organisations (2)

  • Response to solving complex problems has been to centralise

control and assign individual responsibility

  • Individuals have a limited ability to deal with complexity
  • Many of today’s complex problems are beyond the ability of a single

person to cope with

  • Hierarchies are limited by the ability of the commander to deal with

complex environment

  • Best suited to delivery of large scale effect
  • Distribute complexity of the task among many individuals
  • Network structure can have a much greater level of complexity than its

individual elements

  • Greater the number and independence of force elements the more

effective a force is at high complexity missions

  • Local coordination produces local emergent collective behaviour
  • Distributed control is not a panacea
  • Need to determine what the correct balance is for specific mission
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Complex environments – the need to adapt

We need to:

  • rapidly decide, as situations develop, what is to be done, how, who

with, & how to measure success

  • maintain effectiveness under unpredictable and rapidly evolving

conditions, retaining ability to raise additional tasks as needed

  • to rapidly assemble tailored, diverse, multi-disciplinary teams and get

them operational and effective Planning for all eventualities becomes impossible on any reasonable scale of time, system size, or effort

Ability to adapt appropriately is fundamental to success

Requiring:

  • investment in the capability to adapt to the unexpected
  • generation of capabilities that have the capacity to respond effectively to

new and unforeseen challenges

  • moving away from planning and optimising for highly probable events

with a predetermined response

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System

context

System assesses whether change was desirable; keeps or discards change

Outcome of selection encoded in system memory selection Context changes System and context interact System changes

(triggered by outcome

  • f interaction)

System and context interact System senses

  • utcome of “new”

interaction variation sense change sense feedback adopt/discard Concept of fitness

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Counter insurgent conflict ecosystem

Coalition forces Coalition OGDs

International Media

NGOs

National government

Criminal cells Legitimate businesses

Local government

National police National forces Illegitimate business Terrorists National Media Private security co. Local population Ethnic groups Tribal groups Clans Tribal fighters Foreign fighters Refugees Warlords Religious groups Political groups Militia

……. operating at multiple scales Multiple cooperating and competing groups

Hypothetical boundaries for purpose of analysis

Based on Kilcullen D., Counterinsurgency Redux, Small Wars Journal, http://smallwarsjournal.com/documents/kilcullen1.pdf

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Unbounded system; local & global networks & interdependencies

Coalition forces Coalition OGDs International Media NGOs National government Criminals Legitimate businesses Local government National police National forces Illegitimate business Terrorists National Media Private security co. Foreign fighters Local population Ethnic groups Tribal groups Clans Tribal fighters Refugees Warlords Religious groups Political groups Militia

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Open system

Coalition forces Coalition OGDs

International Media

NGOs

National government

Criminals

Legitimate businesses Local government

National police National forces

Illegitimate business

Terrorist National Media

Private security co.

Local population Ethnic groups Tribal groups Clans Tribal fighters Foreign fighters Refugees Warlords Religious groups Resources Support Training Opposition O p p

  • s

i t i

  • n

Political groups Militia Constraints Ideology R e s

  • u

r c e s O p p

  • s

i t i

  • n

Support Intelligence Ideology Training Propaganda Propaganda Intelligence Technology Technology Trade Trade

Open system boundary

enabling

input and output

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Multi‐scale adaptation & co‐ adaptation

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Implications for system analysis

  • Multi‐scale problems
  • So look how to tackle the problem at all scales
  • Combining bottom up (tackling the source of grievance on local scale) and top

down (strategic support to nation in establishing governance) approaches

  • Multi‐dimensional problem space
  • So look for interventions across all the potential dimensions
  • Understand how effects propagate through the system
  • Consider role of intra‐level and inter‐level dynamics
  • Bridge the gap between individual and collective behaviour
  • Interdependence → planning an intervention review the potential

unintended consequences across dimensions & scales not targeted specifically by that action

  • Consider role of adaptation and co‐adaptation affects overall system

behaviour

  • Flow of energy/material/information etc. into system are powerful drivers
  • f self‐organisation and collective behaviour
  • System can only be understood in terms of context
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SLIDE 19
  • Closed system
  • Linear & reductionist approaches enable us to

predict and reproduce system behaviour

  • Behaviour of the whole is the sum of the parts
  • Systems are well mixed and spatial and temporal

behaviour can be averaged

  • Systems don’t adapt
  • Spare capacity = redundancy
  • Environmental conditions can be ignored
  • Behaviours at different scales are independent
  • Control is centralised

CAS approach challenges current assumptions