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Invitation to Research SYSTEMS THINKING Roger Clarke, Xamax Consultancy, Canberra Visiting Professor, CSIS, Uni of Hong Kong Visiting Fellow, Australian.

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Presentation on theme: "Invitation to Research SYSTEMS THINKING Roger Clarke, Xamax Consultancy, Canberra Visiting Professor, CSIS, Uni of Hong Kong Visiting Fellow, Australian."— Presentation transcript:

1 Invitation to Research SYSTEMS THINKING Roger Clarke, Xamax Consultancy, Canberra Visiting Professor, CSIS, Uni of Hong Kong Visiting Fellow, Australian National University Res /15-Sys.ppt ebs, 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/Openness to external Stimuli or Triggers Entropy The tendency to lose energy and order Negentropy The importation of energy to sustain order Unguidedness cf. Purposiveness Adaptiveness/Learning The ability to change as a result of stimuli

5 A Model An Abstract-World Representation of 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 exercising Self-Determination / Free Will e.g. Humans and Organisations

7 Simple Process Model

8 Process Model with Controller

9 Cybernetics Control Loop:
Inputs or Process Parameters changed as 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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