After successful completion of the course, students are able to solve problems algorithmically.

• Students develop an understanding of processes (i.e. sequences of activities) and the spatial scale on which they are happening (concerning past, present, and future).
• The student is able to simplify complex problems into (algorithmically) solvable constituents. He/She is able to model planning problems as models and simulate them in order to gain insight into performance.
• The results are compared using visualization as means.
• Students will have the competence of rapidly developing simulation models in order to answer "what-if" questions. In fact, this knowledge can act as the basis for envisioning novel spatial methods that aid in decision-making.

• Processes: Recording and modeling temporal sequences of (spatial) activities (e.g. as flow-chart, Business Process Modeling Notation).  
• Simulation: Model – Parameters – Solution Space, using a hands-on approach by programming with agent-based simulation software
• Visualization: Comparison and discussion of simulation results as means for decision-making in the planning process

• Introduction to NetLogo, an agent-based programming and simulation environment.
• Developing a "script" according to the needs and specifications of the student.
• Discussion of the results.

In principle, by working on the task.
Specifically, by:

• Presence
• Discussion about the meaningful use of the algorithm
• Presentation