eJournal: uffmm.org,
ISSN 2567-6458, 26.Januar 2019
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

Last Change: 27.February 2019


An overview to the enhanced AAI theory  version 2 you can find here.  In this post we talk about  two different strategies how to proceed in the AAI analysis.


The elaboration of an actor story AS   happens generally during a process driven by some actors, which communicate with each other and the environment. This can be done in various ways. Here we consider two main cases:

  1. Top-down: There exists a group of experts EXPs which will analyze a possible solution, will test these, and then will propose these as a solution for others. During this process they mainly communicate only with the  stakeholder of the problem (and probably with experts from other departments).
  2. Bottom-up: There exists a group of experts EXPs too but additionally there exists a group of customers CTMs which are also the stakeholder of the process and which will be guided by the experts to use their own experience to find a possible solution.

In reality  there can be many forms of collaboration which are mixing these two idealized cases. The top-down paradigm is very common although it produces many problems, especially in communal projects. A bottom-up process including the topic of ‘participation’ in communities and cities is today highly demanded, but not well specified and not a common practice.

In this book  the  bottom-up paradigm will be discussed explicitly.  This requires that the AAI experts collaborate from the beginning with a group of common users from the application domain. To do this they will (i) extract the knowledge which is distributed in the different users, then (ii) they will start some modeling from these different facts to (iii) enable some basic simulations. These simple simulations (iv) will be enhanced to   interactive simulations which allow serious gaming either (iv.a) to test the model or to enable the users (iv.b) to learn the space of possible states. The test case will (v) generate some data which can be used to evaluate the model with regard to pre-defined goals. Depending from these findings (vi) one can try to improve the model further.


The mayor of a city has the identified problem P that there exists a certain road which has a to high load of traffic. He wants to find a new configuration S which minimizes this problem without creating a new problem P’.

He decides to attack this problem not by delegating it to a group of experts only but to a group of experts collaborating with all the citizens which think to be affected by this problem and a possible solution. Thus the mayor opts for a bottom-up approach. This poses the challenge to find a procedure which enables the inclusion of the citizens in the overall process.