Dynamical System Design is an universitary course held for the master's student of management engineering of LIUC University on how to use formal models for decision-making in complex contexts. It combines intuitive system thinking, basic mathematics, and simulation practice with an ad hoc software simulator to turn qualitative reasoning into operational decisions.
A central principle is moving from ad-hoc decision habits to explicit and repeatable engineering logic. The course contrasts "the craftsman" approach with a structured modeling approach that can be discussed, transferred, and improved collaboratively.
The course distinguishes complication from complexity: complication can be reduced by better representation, while complexity is a real property of systems. The task of the modeler is to choose the right abstraction level.
Modeling starts with variables and dependencies, then evolves toward equations and simulation. This phased method makes assumptions explicit before numerical formalization.
A model is useful only if it behaves coherently under alternative scenarios. The course emphasizes validation, what-if analysis, and sensitivity analysis as core quality criteria.
Beer-keg and inventory-style exercises are used to show the difference between estimating outputs and searching for input conditions that achieve a target outcome.
Cases like penalty-kick prediction illustrate how behavior can be inferred from output histories, with probabilistic reasoning and black-box thinking.
Urban dynamics, epidemiological reasoning, queueing in emergency contexts, and competitive market analogies show how models inform policy and managerial trade-offs.
