The course will cover the basic ideas and techniques underlying the design of intelligent machines. By the end of this course, you will have learned how to build autonomous (software) agents that efficiently make decisions in fully informed, partially observable and adversarial settings as well as how to optimize actions in uncertain sequential decision making environments to maximize expected reward.
Lectures: online live Q&As sessions: Wednesdays, 09:00-10:00
https://fu-berlin.webex.com/fu-berlin-en/j.php?MTID=mfec43e35232d893f59bdc090b005b1cb
Tutorials: online live Q&As sessions: Tuesdays, 16:15-17:15
https://fu-berlin.webex.com/fu-berlin/j.php?MTID=meb4f1abaa8da64b31b1af44da3e72e98
Project 2 will be announced on 21/6/2021 and is about implementing adversarial search algorithms. The deadline will be on: 19.07.2021.
Course No | Course Type | Hours |
---|---|---|
19303701 | Vorlesung | 2 |
19303702 | Übung | 2 |
Time Span | 14.04.2021 - 15.10.2021 |
---|---|
Instructors |
Philip Naumann
Eirini Ntoutsi
Arjun Roy
|
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 |
0511a_m72 | 2016, MSc Informatik (Lehramt), 72 LPs |
0511b_m72 | 2019, M-Ed Fach 2 Informatik (Lehramt an Gymnasien - Quereinstieg), 72 LP |
0556a_m37 | 2018, M-Ed Fach 1 Informatik (Lehramt an Integrierten Sekundarschulen und Gymnasien), 37 LPs |
0557a_m42 | 2018, M-Ed 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 |
---|---|---|---|
Wednesday | 8-10 | Online | 2021-04-14 - 2021-07-14 |
Day | Time | Location | Details |
---|---|---|---|
Tuesday | 16-18 | Online | Übung 01 |