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Agenda

Invitation to Research SYSTEMS THINKING Roger Clarke , Xamax Consultancy, Canberra Visiting Professor, CSIS, Uni of Hong Kong Visiting Fellow, Australian National University http://www.anu.edu.au/people/Roger.Clarke/... ...Res /15-Sys.ppt ebs, 16-20 January 2003. Agenda. Systems Models

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Agenda

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  1. Invitation to ResearchSYSTEMS THINKINGRoger Clarke, Xamax Consultancy, CanberraVisiting Professor, CSIS, Uni of Hong Kong Visiting Fellow, Australian National University http://www.anu.edu.au/people/Roger.Clarke/......Res /15-Sys.pptebs, 16-20 January 2003

  2. Agenda • Systems • Models • Cybernetics • Complexity of: • System • Model • Behaviour

  3. A System • A set of interacting Real-World Entities • Interacts with its Environment across its Boundary • Entities within a System: • gather inputs via Sensors • transmit outputs via Effectors • interact with one another via Interfaces • Systems may: • exist at the same level (e.g. an mammal’s cardio-vascular and digestive systems) • be related hierarchically (e.g. corpuscles within blood within the cardio-vascular system)

  4. System Characteristics • Degree of Closedness/Opennessto external Stimuli or Triggers • EntropyThe tendency to lose energy and order • NegentropyThe importation of energy to sustain order • Unguidedness cf. Purposiveness • Adaptiveness/LearningThe ability to change as a result of stimuli

  5. A Model • An Abstract-World Representationof a Real-World System • Iconic or Symbolic/Mathematical • Capable of being: • viewed (e.g. a map • manipulated (e.g. a model aircraft in a wind-tunnel) in ways that the System cannot be • Necessarily (greatly) simplified • ‘The only reliable model of a real-world system is the system itself’ (Pratchett)

  6. Categories of Models • Deterministic Models – Automata • Computable by Analytical Methods • Too Complex to Compute, hence Requiring Numerical Methods • Probabilistic Models • Non-Deterministic / Stochastic Models • Entities exercisingSelf-Determination / Free Wille.g. Humans and Organisations

  7. Simple Process Model

  8. Process Model with Controller

  9. Cybernetics • Control Loop: • Inputs or Process Parameters changedas a result of measurement of Outputs • Feedback:Positive / Reinforcing or Negative / Retardent • Static Equilibrium / Steady-State cf.Dynamic Equilibrium / Homeostasis • Delays, Control Limits, Tolerances => Hunting / Hysteresis, Over-Correction • Feedforward • Tiered Control Loops exhibit Complex Behaviour

  10. Levels of Discourse About Systems (Boulding) • Framework Anatomy • Balanced Dynamic Clockwork • 1st-Order Control Thermostat • Open, Self-Maintaining Cell (in Biology) • Genetic-Societal Plant • Self-Aware, Purposive Animal (& Orgn?) • Self-Conscious Human • ...

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