This course will be in English.
We will study Markov Chains including Birth-, Death processes, Poisson process, Phase-type distributions, Markov decision processes, and queueing models.
This lecture will be on site and in presence. However, videos and materials from the past exist and can be used, if you miss a lecture. There is no guarantee that we will cover exactly and only this material.
All existing videos can be found in the Markov Chains folder in the FU Box: https://box.fu-berlin.de/s/nE2ieRKPYkW4c8e . The following plan may still change.
Week 1: (15.04.-17.04.2025) Introduction (slides in resources),
Lecture 1: Probability theory primer part 1 (lecture notes in resources).
Lecture 2: Probability theory primer part 2, Moments.
There will be no lectures on 24.04. and 26.04.2025
Week 2 (29.04.2025):
Lecture 3: Generating Functions, Minimum and Maximum of RV, Discrete probability distributions.
Week 3 (06.05.2025):
Lecture 4: Continuous probability distributions, reliability theory.
Week 4 (13.05.-15.05.2025):
Part b: Phase-type distributions
Lecture 5: Bounds and limit theorems:
Lecture 6: Discrete time Markov chains
Week 5 (20.05-22.05.2025):
Lecture 7: DTMCs, Sojourn times and embedded MCs
Lecture 8: DTMCs Classification of states
Lecture 9: DTMCs, Irreducibility, Potential and Fundamental matrix
Lecture 10: Random Walk
Week 6 (27.05.2025):
No lecture on 29.5.2025.
Lecture 11: Limiting and stationary distributions
Lecture 12: Reversibility
Lecture 13: Page rank
Markov Decision Processes (MDPs) Material by David Silver.
Week 7 (03.06.-05.06.2025):
Lecture 14: CTMCs
Lecture 15: Renewal processes, PP, uniformisation, stochastic Petri nets
Week 8 (10.6.-12.06.2025):
Lecture 16:
Petri net tool PIPE2:
Lecture 17: Basic queueing theory
Week 9 (17.6.-19.06.2025):
Lecture 18: Basic queueing theory (Part 2)
Lecture 19: The M/M/1 queue
Week 10 (24.06.-26.06.2025):
Lecture 20: The M/M/m queue
Lecture 21: The M/M/m/K queue
Week 11 (01.07.-03.07.2025):
Lecture 22: The M/G/1 queue
Lecture 23: Open queueing networks
Week 12 (08.07.-10.07.2025):
Lecture 24 Closed Queueing Networks
Week 13 (15.07.-17.07.2025):
Lecture 25 Mean Value Analysis
17.07.2025: 10-12 Exam
William Stewart. Probability, Markov Chains, Queues and Simulation. Princeton University Press 2009.
Course No | Course Type | Hours |
---|---|---|
19326601 | Vorlesung | 4 |
19326602 | Übung | 2 |
Time Span | 15.04.2025 - 17.07.2025 |
---|---|
Instructors |
Justus Purat
Katinka Wolter
|
0086c_k150 | 2014, BSc Informatik (Mono), 150 LPs |
0086d_k135 | 2014, BSc Informatik (Mono), 135 LPs |
0087d_k90 | 2015, BSc Informatik (Kombi), 90 LPs |
0088d_m60 | 2015, MSc Informatik (Kombi), 60 LPs |
0089b_MA120 | 2008, MSc Informatik (Mono), 120 LPs |
0089c_MA120 | 2014, MSc Informatik (Mono), 120 LPs |
0207b_m37 | 2015, MSc Informatik (Lehramt), 37 LPs |
0208b_m42 | 2015, MSc Informatik (Lehramt), 42 LPs |
0458a_m37 | 2015, MSc Informatik (Lehramt), 37 LPs |
0471a_m42 | 2015, MSc Informatik (Lehramt), 42 LPs |
0556a_m37 | 2018, M-Ed Fach 1 Informatik (Lehramt an Integrierten Sekundarschulen und Gymnasien), 37 LPs |
0556b_m37 | 2023, M-Ed Informatik Fach 1 (Lehramt an Integrierten Sekundarschulen und Gymnasien), 37 LP |
0557a_m42 | 2018, M-Ed Fach 2 Informatik (Lehramt an Integrierten Sekundarschulen und Gymnasien), 42 LPs |
0557b_m42 | 2023, M-Ed Informatik Fach 2 Informatik (Lehramt an Integrierten Sekundarschulen und Gymnasien), 42 LPs |
0590a_MA120 | 2019, MSc Data Science, 120 LP |
0590b_MA120 | 2021, MSc Data Science, 120 LP |
Day | Time | Location | Details |
---|---|---|---|
Tuesday | 12-14 | T9/Gr. Hörsaal | 2025-04-15 - 2025-07-15 |
Thursday | 10-12 | T9/SR 005 Übungsraum | 2025-04-17 - 2025-07-17 |
Day | Time | Location | Details |
---|---|---|---|
Tuesday | 14-16 | A6/SR 007/008 Seminarraum | Übung 01 |