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All policies make sense based on their underlying assumptions; otherwise no one would be tempted to formulate them or carry them out. Yet, they often have unforeseen consequences that lead to very different outcomes than the ones imagined. Worse, unlike the characters in folk tales who end up realizing their mistake, the unforeseen consequences of policies are typically diffuse and indirect, therefore difficult to trace to their causes. In this fashion, we become lost in a maze of unforeseen consequences.

from this blog post.

The value of System Dynamics is exactly to surface the underlying assumptions, thus minimizes the unforeseen consequences.


Jay W. Forrester’s “Learning Through System Dynamics as Preparation for the 21st Century” may give you a clue:
the latest version as mentioned by Bill Harris.

A very good introductory book of systems thinking by Donella Meadows after I peeked some pages from
Google Books.

Some lectures about the exponential growth. There are 8 parts in this series.

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System Dynamics (SD) can be seen as one kind of visual representation of nonlinear control (or nonlinear dynamics in Physics), especially for application on social problems (management, economics, politics, etc). Therefore it is no surprise to find that many System Dynamicists have natural sciences or engineering background. In fact, Jay W. Forrester himself was an engineer.

While System Dynamicists commonly use software such as Vensim, iThink (Stella) and Powersim, it is actually tool independent and can be implemented in many ways.

Here is an implementation of SD library using Modelica (open source competitor of MATLAB). While it is still quite basic and not customized for SD quick use, it is probably a good bridge for newcomers to learn SD if they come from engineering background. Its interface is similar to engineering software.

For a quick glance, check out its slides and paper.

If you want to try out:

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