Course syllabus

EDAP01 + TFRP20: Artificial Intelligence

Welcome to the course EDAP01 / TFRP20 Artificial Intelligence

This page should be considered to be the course's home page. All general information will be posted here; note though that you need to be a registered student on the course to get access to the actual course material for the academic year 2024/25.

The first course session starts on Wednesday, January 22nd, 2025, at 15:15 in E:A. Note that attendance is compulsory, and an absolut necessity to keep your place in the course if you were admitted through "antagningen.se" to TFRP20, i.e. if you are external to LTH and / or take the course as optional (fristående) and have received the respective welcome e-mail. Contact the course responsible if you (for a good reason, i.e. illness or family emergency) cannot make it.

More information will come in due time, consider this page a living document, in particular until Friday, January 24th.

General Information

Official course programme: EDAP01 (in Swedish) or EDAP01 (in English). (TFRP20 is identical, but refers to the "individual course", fristående kurs, as opposed to LTH's programme courses.) This course is also given as EDAF70F to PhD students, but the requirements for passing are slightly different than for undergraduates. See below or contact Elin for details.

The course textbook is Artificial Intelligence: A Modern Approach (aka AIMA), 4th ed., by Stuart Russell and Peter Norvig, ISBN-13 978-1-292-40113-3, or ISBN-101-292-40113-3

The course is given in English.

The exam will be held on 19th of March 2025, re-exam is scheduled for August 26th. Please note that as of academic year 2024/25 the exam is compulsory for all attendees. To receive full course credits, you will have to pass all programming / homework assignments and the exam. It will be possible to hand in one assignment late (details below). 

This year's course will be given by Elin A. Topp, Jacek Malec, Pierre Nugues and Stefan Larsson. Some lectures (see below) will be given by PhD candidate Simon Kristoffersson Lind. We will have eight TAs (alphabetically): Faseeh Ahmad, Esranur Erturk, Ayesha Jena,  Wietze Koops, Simon Kristoffersson Lind, Leonard Papenmeier, Eliot Petrén, and Momina Rizwan. Elin A. Topp is the teacher officially responsible for the course (kursansvarig), but also Jacek Malec can help out with a lot of information. The contact info can be found on each teacher's home page.

There is an open Canvas page for the course, containing basic information and links: PermanentInfoEDAP01 In particular, the TimeEdit schedule can also be found there.

Discord server for discussions, resource and contact hours, and QA: tba

Syllabus

There will be three combined programming and reading/writing assignments, roughly devoted to search, probabilistic reasoning in time, and basics of ML. The assignments are expected to be submitted via Canvas. The assignments will be evaluated by the TAs and approved by some teacher. You need to have all assignments approved and pass the exam to get the full course credits (7.5), the final grade will be based on the exam result. There will be a chance to submit only ONE assignment late (before the re-exam in August) - check the details in intro slides from the first lecture.

Any questions related to the assignments should be addressed in the first place to the TAs responsible for the assignment  during the scheduled resource hours (twice a week). You may also contact the responsible teacher, either during contact hours or via email.

Administrative questions (registration, etc) may be adressed to expedition@cs.lth.se, or to the course responsible (EAT).

In the description below the teachers are denoted by the following acronyms:

  • EAT - Elin Anna Topp
  • JM - Jacek Malec
  • PN - Pierre Nugues
  • SL - Stefan Larsson
  • SKL - Simon Kristoffersson Lind

 

 

Plan of the lectures
Date No. Lecture Who AIMA chapter
22/1 1 Introduction. Agents. EAT 1, 2
24/1 2 Search JM 3 , 4
29/1 3 Advanced search, games SKL 6
31/1 4 Logic, reasoning JM 7, 8.1-8.2
5/2 5 Probabilistic representation and reasoning SKL 12, 13.1-3
7/2 6 Probabilistic reasoning over time (HMMs) SKL 14
12/2 7 Probabilistic Robotics EAT 14, 26
14/2 8 Machine Learning 1 PN 1/2 of 19
19/2 9 Machine Learning 2 PN 1/2 of 19 and 22
21/2 10 Semantic Technology PN 1/2 of 10
26/2 11 NLP PN 24, 25
28/2 12 Ethics and AI SL 28
5/3 13 Knowledge Representation JM 10
7/3 14 AI and Robotics @ LU EAT 26
10/3 15 TBA TBA
19/3   Exam  
26/8 Re-exam

 

Course summary:

Date Details Due