Friday, March 23, 2007

IE 602 System Dynamics Lecture Notes 2007-01 - By Yaman Barlas

These are my lecture notes of the 7. session of IE 602 System Dynamics Analysis and Design course in Industrial Engineering Graduate Program of Bogazici University. You can find the video of the lecture in Google Videos. The course is given by Prof. Yaman Barlas.

Links to the videos:
Part I
Part II (Turkish)
Part III (Turkish)

Interactive Gaming:
There is evidence that we human beings cannot make efficient decisions in complex feedback systems. By this we mean, we make a decision, we observe the results then we give another decision. These are feedback problems. In dynamic feedback decision problems, system has its life on own. System reacts to input and does all sorts of things as a result of feedbacks. You make a decision. system reacts. And you observe. Most feedback structures are nonlinear and delayed. When you combine them, we are not good decision makers. We under perform.
Controlled experiments may yield what kind of decisions decision makers ignore, overemphasize, utilize, have misperceptions, are there some generalizable inadequacies common to human decisions? These are decision making, cognitive questions. They are research questions we can research them in a controllable lab environment. This is phase 1.

Phase II is how can we excite learning in experiential environments. Is it possible to enhance learning in them? To what extent is it possible? Or is it possible at all You may think learning has occurred, but person only learned mechanics of the game. Here we men learning as understanding dynamic causalities, what structures play a role in this dynamic behavior of the system. That understanding we call learning.
We don't call learning, imitating some past successful actions. You don't understand dynamics of the causality structure. you may discover the mechanical tricks somehow. But you don't know why it works. You cannot transfer this knowledge to another problem setting.
By learning we mean understanding what goes on in the system.

Is that possible by game? That is interesting ques but not trivial. How can I separate learning from mechanical learning.

Finally we can make use of interactive games to cast some decision rules. Interactive games re nice platforms to test these rules.

You can use interactive gaming to test validity and robustness of models. Professionals in the field can test the model by using the games. That is a nice way of stress testing the model. These subjects can find uncovered structures.

Potential pitfalls in interactive gaming:
IG can be a fantastic tool if properly used. But it is very easy to misuse it.
1. People tend to forget that there is a model engine behind the screen. They can think that nicely designed user interfaces with a lot of informations are sufficient.
2. If you don't spend enough time to explain the problem setting, model and the game, their performance will be masked, negatively influenced by their ignorance of the actual problem in the model. Then they cannot further progress.
3. Preoccupation with technology. We are not in the commerce of games.
4. As a corollary of preoccupation with technology: Game mechanics become too complicated. Game should not be difficult to play.
5. Video game syndrome. The players aim to beat the game and get the highest score. Learning is not the aim.


Dupa Jasia said...

.. .. ...

Justin Lyon said...

THe UI is essential, but you are right that people don't understand that a model of the 'physics' of reality - whether SD, ABM, DES or a hybrid must rest behind the scenes to make it all work. I've started to just accept the fact that the UI sells the recommendations - without it you get no buy in - group model building also helps. I mean, even Jay Forrester had problems convincing people that the sims were the source of his inspiration!

Justin Lyon said...
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