 | Study programme 2018-2019 | Français | |
 | Discrete Event Systems | ||
Activité d'apprentissage à la Faculty of Engineering |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) |
|---|---|---|---|
| I-TCTS-100 |
|
|
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Anglais | Anglais | 14 | 22 | 0 | 0 | 0 | Q1 |
Content of Learning Activity
REVIEW OF SYSTEM THEORY FUNDAMENTALS: Basic concepts<em>, Time-driven</em> vs. <em>event-driven</em> systems, Examples of Discrete Event Systems (DES): automated manufacturing; traffic systems, The queueing system model. UNTIMED MODELS OF DISCRETE-EVENT SYSTEMS, State Automata, Analysis: stability, reachability, deadlocks. The Poisson counting process and Markov chain models INTRODUCTION TO DISCRETE EVENT (MONTE-CARLO) SIMULATION, Basic concepts in discrete event simulation, Model construction and applications, Introduction to estimation theory MARKOV DECISION PROCESSES. Solving resource contention problems: admission control, routing, scheduling
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Not applicable
Mode of delivery
- Face to face
Type of Teaching Activity/Activities
- Cours magistraux
- Exercices dirigés
- Utilisation de logiciels
- Travaux pratiques
- Etudes de cas
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)