رویکرد دینامیک سیستمها به «مدل سازی»
پرسشهای این درس
کتابها و مقالاتی که در این جلسه ارایه میشوند:
1985, Jay W. Forrester, "The" Model Versus a Modeling "Process"
19۹4, John Sterman, Learning In and About Complex Systems
2001, John Sterman, System Dynamics
Modeling:
Tools For Learning In a Complex World
2002, John Sterman, All models are wrong: reflections on
becoming a systems scientist
2010, Ali N. Mashayekhi, Soheil Ghili, System dynamics problem definition as an evolutionary process using the concept of ambiguity
2001, John Sterman, System Dynamics
Modeling:
Tools For Learning In a Complex World
2002, John Sterman, All models are wrong: reflections on
becoming a systems scientist
2010, Ali N. Mashayekhi, Soheil Ghili, System dynamics problem definition as an evolutionary process using the concept of ambiguity
2010, Ali N. Mashayekhi, Soheil Ghili, System dynamics problem definition as an evolutionary process using the concept of ambiguity
"The" Model Versus a Modeling "Process"
1985, Jay W. Forrester, "The" Model Versus a Modeling "Process"
- Emphasis on "The" Model is Unrealistic and Alarming
- Published Models are only a snapshot in time from a continuously evolving set of ideas about a social system.
- The Models are always in a continuous state of evolution.
- Each question, each reaction, each new input of information, and each difficulty in explaining the models leads to modification, clarification, and extention.
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We are proposing the "Process" of Modeling rather than particular frozen and final models.
- Models will help to clarify our processes of thought
- Make explicit the assumptions we are already making
- Show the consequences of the assumptions
- As our understanding, our assumptions, and our goals change, the models can change.
- For real life implementation, we can expect that there will be a series of models simultaneously existing and simultaneously in evolution.
- Process of Modeling as a continuing companion to, and tool for, the improvement of judgment and human decision making
Learning In and About Complex Systems
19۹4, John Sterman, Learning In and About Complex Systems
- Learning is a feedback process
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Barriers to Learning
- Dynamic Complexity
- Limited Information
- Confounding variables and ambiguity
- Misperceptions of Feedback
- Flawed Cognitive Maps of Causal Relations
- Erroneous Inferences about dynamics
- Unscientific Reasoning; Judgmental errors and biases
- Defensive Routines and Interpersonal Impediments to Learning
- Implementation failure
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Requirements for successful learning in complex systems
- Improving the Learning Process
- Pitfall of the Virtual Worlds
- The necessity of Simulation
System Dynamics Modeling: Tools For Learning In a Complex World
2001, John Sterman, System Dynamics Modeling: Tools For Learning In a Complex World
- Dynamic Complexity
- Feedback
- Time Delays
- Stocks and Flows
- Attribution Errors and False Learning
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Tools of System Dynamics
- Causal Loop Diagram
- Causal Diagram Showing Stock and Flow Structure
- Model Equations
- Simulation
- Applications
All models are wrong: reflections on becoming a systems scientist
2002, John Sterman, All models are wrong: reflections on becoming a systems scientist
- Systems thinking and modeling for a complex world
- Policy resistance
- (Almost) nothing is exogenous
- Bathtub dynamics
- Model boundary: Invisible fences in the mind
- Model testing
- A hard look at soft variables
- Why simulation is essential
- All decisions are based on models ... and all models are wrong
- The importance of ‘‘Why’’ questions
System dynamics problem definition as an evolutionary process using the concept of ambiguity
2010, Ali N. Mashayekhi, Soheil Ghili, System dynamics problem definition as an evolutionary process using the concept of ambiguity
- The Concept of Ambiguity
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The Role of Ambiguity in Problem Definition and Model Building Process
- The Role of Ambiguity in Selecting Main Variables
- The Role of Ambiguity in Momentum Policies
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The Role of Ambiguity in Using Dynamic Model to Finding Solutions for Difficulties
- The Role of Ambiguity in Model Analysis
- An Example: Problem Definition for Real Estate Bubble
- Some Guidelines to Use Ambiguity to Enrich Problem Definition
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