lunduniversity.lu.se

Computer Science

Faculty of Engineering, LTH

Denna sida på svenska This page in English

Course material

The material here will made available when it is ready. For previous years' slides (specifically those where there is no update for 2019), see below.

2019 Lectures

.
DateNo.LectureWhoSlidesComment
23/11Introduction. Agents.JMIntro, Ch2. intro updated
1/24Probabilistic representation and reasoningEATPRR Added two slides on notation to clarify confusing point about vector / distribution notations
6/25Probabilistic reasoning over time (HMMs)EATReasoning over time / HMMs checked the notation for pointwise multiplication of vectors and clarified it
8/26Logic, ReasoningJMCh7plain Chapter 7
13/27Machine Learning 1PN[pdf]
15/28Machine Learning 2PN[pdf]
20/29Knowledge RepresentationJMmotivation, summary, KRminor updates
27/211Natural language processingPN[pdf] [pdf]
1/312Semantic technologyPN [pdf]
6/313(Probabilistic) RoboticsEATProbRob
1/24(Not so probabilistic) RoboticsEATRob
11/315Fairness in AISL[slides]

2018 Lectures

DateNo.LectureWhoSlides
17/11Introduction. Agents.JMIntro, Ch2.
19/12SearchJMCh3, Ch4.
24/13Games, Constraint SatisfactionJMCh5, Ch6.
26/14Logic, ReasoningJMIntro, Ch7.
31/15AI in Robot(ic)sEATAI-Rob
2/26Probabilistic representation and reasoningEATPRR
7/27Machine Learning 1PN[pdf]
9/28Machine Learning 2PN[pdf]
14/29Probabilistic reasoning over time (HMMs)EATHMM
16/210Bayesian LearningEATBLearn
21/211Knowledge RepresentationJMreasoning, KR
23/212PlanningJMPlanning.
28/213NLP 1PN[Part 1] [Part 2]
2/314NLP 2PN[Part 3] [Part 4]

2017 Lectures

DateNo.LectureWhoSlides
18/11Introduction. Agents.JMIntro, Ch2.
20/12SearchJMCh3, Ch4.
25/13Games, Constraint SatisfactionJMCh5, Ch6.
27/14Logic, ReasoningJMCh7.
1/25Machine Learning 1PN[pdf]
3/26Machine Learning 2PN[pdf]
8/27Knowledge RepresentationJMFOPL, KR.
10/28PlanningJMPlanning.
15/29Probabilistic representation and reasoningEATPRR
17/210Probabilistic reasoning over time (HMMs)EATHMM
22/211Bayesian LearningEATBLearn
24/212AI in Robot(ic)sEATAI-Rob
1/313NLP 1PN[Part 1] [Part 2]
3/314NLP 2PN[Part 3] [Part 4]

2016 Lectures

DateNo.LectureWhoSlides
19/11Introduction. Agents.JMIntro, Ch2.
21/12Search 1JMCh3, Ch4.
26/13Probabilistic representationEAT[pdf]
28/14Games, Constraint Satisfaction ProblemsJMCh5, Ch6.
2/25Bayesian learningEAT[pdf]
4/26Logic, reasoningJMCh7.
9/27Hidden Markov modelsEAT[pdf]
11/28Knowledge representationJMCh8, KBS.
16/29Machine learning 1PN[pdf]
18/210Machine learning 2PN[pdf]
23/211PlanningJMPlanning, Ch11
25/212RoboticsEAT
1/313Natural language processing 1PN[Part 1] [Part 2]
3/314Natural language processing 2PN[Part 3] [Part 4]


2015 Lectures

DateNo.LectureWhoSlides
20/1 1Introduction. Agents. JMIntro, Ch2.
23/1 2Search 1 JMCh3.
27/1 3Search 2 JMCh4, Ch5.
30/1 4Logical agents JMCh6, Ch7.
3/2 5Logic, KR JMCh8, KBS.
6/26Probabilistic representationsEAT [pdf]
10/27AI and real-life problems LHExpertMaker.
13/28Bayesian learningEAT[pdf]
17/29Hidden Markov modelsEAT[pdf]
20/210RoboticsEAT[pdf]
24/211Machine learning (Lect. 1)PN[pdf]
27/212Machine learning (Lect. 2)PN[pdf]
3/313Natural language processing (Lect. 1)PN[Part 1] [Part 2]
6/314Natural language processing (Lect. 2)PN[Part 3] [Part 4]


2014 Lectures

DateNo.LectureWhoSlides
21/1 1Introduction. Agents. JMIntro, Ch2.
24/12Search JMCh3
28/13Search, Games.JMCh4, Ch5.
31/14CSP, Logic.JMCh6, Ch7
4/25Probabilistic representationEAT [pdf]
7/2 6 Bayesian learning EAT [pdf]
11/2 7 Machine learning 1. AIMA: 18.1-5. PN [pdf]
14/2 8 Machine Learning 2. AIMA: 18.6-12. PN [pdf]
18/2 9 Logic, resoning, KR JM Ch8, Ch9
21/2 10 Planning JM Planning
25/211KR, Knowledge-Based SystemsJMKBS
28/212NLP 1PNPart 1 and Part 2
4/313NLP 2. AIMA: 22 and 23.PNPart 3 and Part 4. DCG programs
7/314RoboticsEAT


2013 Lectures

DateNo.LectureWhoSlides
21/1 1 Introduction. Agents. JM
24/12Search JM
28/13Search: Ch4, Ch5, Ch6.JM
31/14Logic. Reasoning, Ch7 of AIMA.JM
4/25Knowledge Representation: Ch8, KBSJM
7/2 6 Probabilistic representation EAT [pdf]
11/2 7 Machine learning 1. AIMA: 18.1 to 18.5. PN [pdf]
14/2 8 Machine Learning 2. AIMA: 18.6 to 18.12. PN [pdf]
18/2 9 Bayesian learning EAT [pdf]
21/2 10 Planning JM
25/211NLP 1PNPart 1 and Part 2
28/212RoboticsEAT
4/313NLP 2. AIMA: 22 and 23.PNPart 3 and Part 4. DCG programs
7/314Knowledge-Based Systemsguest

2012 lectures

DateNo.LectureWho
19/1 1 Introduction. Agents. Ch2 of AIMA. JM
26/1 2 Search 1, Chapter 3 of AIMA. JM
2/2 3 Constraint Satisfaction, Chapter 6 of AIMA. JM
9/2 4 Search 2, Chapter 4 and Chapter 5 of AIMA. JM
16/2 5 Logic. Deduction, Ch7 of AIMA. JM
23/2 6 Knowledge Representation, Chapter 8 of AIMA, KBS. JM
24/2 7 Knowledge-Based Systems, an Industry Perspective. guest
1/3 8 KBS recap, Classical Planning (Ch10 of AIMA). JM
15/3 9 Planning 2, Chapter 11 of AIMA. JM
22/3 11 Machine learning 1. AIMA: 18.1 to 18.5. Slides PN
29/3 12 Machine Learning 2. AIMA: 18.6 to 18.12. Slides PN
19/4 10 Probabilistic representation Slides (AIMA 13, 14.1-3) EAT
26/4 13 Machine Learning 3: AIMA: 21 (and a little 17) Slides EAT
2/5 14 Natural Language Processing 1. Slides: Part 1 and Part 2 PN
3/5 15 Natural Language Processing 2. AIMA: 22 and 23. Slides: Part 3 and Part 4. DCG programs. PN
10/5 16 Robotics. AIMA: Chapter 25. Slides EAT