CS2013-final-report

• Formal models and modeling techniques: mathematical descriptions involving simplifying assumptions
and avoiding detail. Examples of techniques include:
o Monte Carlo methods
o Stochastic processes
o Queuing theory
o Petri nets and colored Petri nets
o Graph structures such as directed graphs, trees, networks
o Games, game theory, the modeling of things using game theory
o Linear programming and its extensions
o Dynamic programming
o Differential equations: ODE, PDE
o Non-linear techniques
o State spaces and transitions
• Assessing and evaluating models and simulations in a variety of contexts; verification and validation of
models and simulations
• Important application areas including health care and diagnostics, economics and finance, city and urban
planning, science, and engineering
• Software in support of simulation and modeling; packages, languages
Learning Outcomes:
1. Explain and give examples of the benefits of simulation and modeling in a range of important application
areas. [Familiarity]
2. Demonstrate the ability to apply the techniques of modeling and simulation to a range of problem areas.
[Usage]
3. Explain the constructs and concepts of a particular modeling approach. [Familiarity]
4. Explain the difference between validation and verification of a model; demonstrate the difference with
specific examples 1 . [Assessment]
5. Verify and validate the results of a simulation. [Assessment]
6. Evaluate a simulation, highlighting the benefits and the drawbacks. [Assessment]
7. Choose an appropriate modeling approach for a given problem or situation. [Assessment]
8. Compare results from different simulations of the same situation and explain any differences. [Assessment]
9. Infer the behavior of a system from the results of a simulation of the system. [Assessment]
10. Extend or adapt an existing model to a new situation. [Assessment]
1 Verification means that the computations of the model are correct. If we claim to compute total time, for example,
the computation actually does that. Validation asks whether the model matches the real situation.
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