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Modelling and Simulation

Code: M.EIC038     Acronym: MS

Keywords
Classification Keyword
OFICIAL Artificial Intelligence

Instance: 2021/2022 - 1S Ícone do Moodle Ícone  do Teams

Active? Yes
Responsible unit: Department of Informatics Engineering
Course/CS Responsible: Master in Informatics and Computing Engineering

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
M.EIC 26 Syllabus 2 - 6 39 162

Teaching language

English

Objectives

The goals of this course unit are:


  • to present the basic concepts of modelling and simulation and their areas of application;

  • to present the different phases of the life cycle of a simulation project;

  • to present the main types of models and their adequacy to the treatment of different problems;

  • to present the main architectural aspects of modelling and simulation tools;

  • to introduce modelling and simulation tools.


Learning outcomes and competences

After the successful completion of this course unit, students should be capable of:


  • Identifying problems, developing models and simulation projects;

  • Analysing and applying simulation results;

  • Including simulation techniques in the scientific method of different areas of research;

  • Showing their knowledge of the main areas of interest and current challenges in the area of modelling and simulation;

  • Using modelling and simulation tools;

  • Designing and implementing tools and simulation environment for special or general purposes;

  • Designing, implementing and evaluating simulation projects.


Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

There is no mandatory prerequisite. Knowledge of (object-oriented) programming and statistics are desirable.

Program


  1. Review and presentation of concepts:


    1. Simulation as an engineering methodology;

    2. Modelling (realism, abstraction) and types of models (normative, behavioural….);

    3. Modelling metaphors and simulation techniques;

    4. Data preparation and treatment;

    5. Modelling of complex systems and stochastic processes;


  2. Simulation projects:


    1. Basic techniques of simulation: continuous, discrete and probabilistic simulation;

    2. Simulation life cycle: data modelling, collection and preparation; test, calibration and validation of models, results analysis and implementation;

    3. Languages and environments of simulation.


  3. Advanced topics in modelling and simulation:


    1. Object-oriented simulation;

    2. Distributed simulation;

    3. Visual interactive modelling and simulation;

    4. Intelligent simulation;

    5. Agent-based modelling and simulation;

    6. Simulation environments and simulation of environments;


  4. Advanced applications of simulation;

  5. Project.

Mandatory literature

Brito António Ernesto da Silva Carvalho; Simulação por computador. ISBN: 972-98726-2-7
Law Averill M.; Simulation modeling and analysis. ISBN: 0-07-059292-6
Chung Christopher A.; Simulation modeling handbook. ISBN: 978-0-203-49646-6
Banks Jerry 070; Discrete-event system simulation. ISBN: 0-13-088702-1

Complementary Bibliography

Various Authors; Papers in Conferences and Scientific Journals, ACM SIGSIM, SCS, IEEE, Eurosis

Teaching methods and learning activities

Teaching methodology will include:


  • Theory classes, to present and to discuss conceptual aspects;

  • Practical tutorial-based classes, to develop a simulation project;

  • Development of a simulation project;

  • Writing-up of project report, in paper format;

  • Oral presentation of project results.

Software

Mesa: Agent-based modeling in Python
Repast simulation suite
SimPy: Discrete event simulation for Python
NetLogo multi-agent programmable modeling environment
SUMO: Simulation of Urban MObility
MATSim: large-scale agent-based transport simulations

keywords

Physical sciences > Computer science > Modelling tools
Technological sciences > Engineering > Simulation engineering

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation Weight (%)
Trabalho escrito 20,00
Trabalho prático ou de projeto 50,00
Apresentação/discussão de um trabalho científico 10,00
Teste 20,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Apresentação/discussão de um trabalho científico 12,00
Elaboração de projeto 63,00
Estudo autónomo 24,00
Frequência das aulas 39,00
Trabalho de investigação 24,00
Total: 162,00

Eligibility for exams

To be admitted in the assessment process, students have to reach markings >=8.0 in the continuous assessment (CA) components.

Calculation formula of final grade

Evaluation components:


  • Project development (P): 50%

  • Project report/paper (R): 20%

  • Project demo/presentation and discussion (D): 10%

  • Individual assessment test (T): 20%



Final mark: F = 0.5*P + 0.2*R + 0.1*D + 0.2*T

Examinations or Special Assignments


  • Paper writing-up;

  • Project development;

  • Oral presentation of project results;

  • Individual assessment teset.

Special assessment (TE, DA, ...)

Students with especial satatus should present project, paper and oral demonstration of results, according to the assessment system of the course unit.

Classification improvement

Improvments in classification require improvements in the project and paper components, respectively.

Observations

The kick-off class for the Modelling & Simulation course will be held on October 18, on Zoom, at the following link:

https://videoconf-colibri.zoom.us/j/81461186136?pwd=enVHMXVIaEdpbDQwZ09OMlIrTnBaUT09

Class starts at 9.30 am.
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