Artificial Intelligence (AI-2) SS 2021 /CoursesID:2095
- Most recent entry on 2021-07-09

Organisational Unit

Professur für Wissensrepräsentation und -verarbeitung

Recording type

Vorlesungsreihe

Via

Free

Language

The second semester of the general AI course at FAU, held Summer Semester 2021.

Course chapters

Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Recap Clip 3.1: Sources of Uncertainty
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:02:20
2
Recap Clip 3.2: Recap: Rational Agents as a Conceptual Framework
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:01:34
3
Recap Clip 3.3: Agent Architectures based on Belief States
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:38
4
Recap Clip 3.4: Modeling Uncertainty
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:09:52
5
Recap Clip 3.5: Acting Under Uncertainty
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:38
6
Recap Clip 3.6: Agenda for this Chapter: Basics of Probability Theory
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:01:07
7
Recap Clip 3.7: Unconditional Probabilities (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:26
8
Recap Clip 3.8: Unconditional Probabilities (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:09:58
9
Recap Clip 3.9: Conditional Probabilities
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:01:21
10
Recap Clip 3.10: Independence
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:40
11
Recap Clip 3.11: Basic Probabilistic Reasoning Methods
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:12:07
12
Recap Clip 3.12: Bayes' Rule
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:02:26
13
Recap Clip 3.13: Conditional Independence
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:09:11
14
Recap Clip 4.1: Introduction
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:02:41
15
Recap Clip 4.2: What is a Bayesian Network?
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:12
16
Recap Clip 4.3: What is the Meaning of a Bayesian Network?
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:33
17
Recap Clip 4.4: Constructing Bayesian Networks (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:52
18
Recap Clip 4.5: Constructing Bayesian Networks (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:08:17
19
Recap Clip 4.6: Inference in Bayesian Networks
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:55
20
Recap Clip 4.7: Conclusion
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:04:57
21
Recap Clip 5.1: Introduction
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:08
22
Recap Clip 5.2: Rational Preferences
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:02:04
23
Recap Clip 5.3: Utilities and Money (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:51
24
Recap Clip 5.4: Utilities and Money (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:00
25
Recap Clip 5.5: Multi-Attribute Utility (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:03
26
Recap Clip 5.6: Multi-Attribute Utility (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:38
27
Recap Clip 5.7: Decision Networks
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:14:48
28
Recap Clip 6.?: Modeling Time and Uncertainty
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:11:11
29
Recap Clip 6.3: Inference: Filtering, Prediction and Smoothing (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:57
30
Recap Clip 6.4: Inference: Filtering, Prediction and Smoothing (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:32
31
Recap Clip 6.5: Inference: Filtering, Prediction and Smoothing (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:06
32
Recap Clip 6.6: Hidden Markov Models (Part 1)
Dr.-Ing. Dennis Müller
2021-03-30
Free
00:08:14
33
Recap Clip 6.7: Hidden Markov Models (Part 2)
Dr.-Ing. Dennis Müller
2021-03-30
Free
00:10:39
34
Recap Clip 6.8: Dynamic Bayesian Networks
Dr.-Ing. Dennis Müller
2021-03-30
Free
00:07:19
35
Recap Clip 7.1: Making Complex Decisions
Dr.-Ing. Dennis Müller
2021-03-30
Free
00:01:23
36
Recap Clip 7.2: Sequential Decision Problems
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:07:07
37
Recap Clip 7.4: Value/Policy Iteration
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:04:42
38
Recap Clip 7.5: Partially Observable MDPs
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:16
39
Recap Clip 7.6: Online Agents with POMDPs
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:08:15
40
Recap Clip 8.2: Forms of Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:11:22
41
Recap Clip 8.3: Inductive Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:58
42
Recap Clip 8.4: Learning Decision Trees
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:04:35
43
Recap Clip 8.5: Using Information Theory (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:10
44
Recap Clip 8.6: Using Information Theory (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:07:23
45
Recap Clip 8.7: Evaluating and Choosing the Best Hypothesis (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:10
46
Recap Clip 8.8: Evaluating and Choosing the Best Hypothesis (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:09:40
47
Recap Clip 8.9: Computational Learning Theory (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:05:01
48
Recap Clip 8.10: Computational Learning Theory (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:04
49
Recap Clip 8.11: Regression and Classification with Linear Models (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:31
50
Recap Clip 8.12: Regression and Classification with Linear Models (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:02:30
51
Recap Clip 8.13: Regression and Classification with Linear Models (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:04:55
52
Recap Clip 8.14: Artificial Neural Networks (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:09:49
53
Recap Clip 8.15: Artificial Neural Networks (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:12
54
Recap Clip 8.16: Artificial Neural Networks (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:23
55
Recap Clip 8.17: Artificial Neural Networks (Part 4)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:08:24
56
Recap Clip 8.18: Support Vector Machines
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:12:16
57
Recap Clip 9.1: Full Bayesian Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:11:41
58
Recap Clip 10.1: Logical Formulations of Learning (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:07:52
59
Recap Clip 10.2: Logical Formulations of Learning (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:00:58
60
Recap Clip 10.3: Explanation-Based Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:26
61
Recap Clip 10.4: Relevance-Based Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:13:33
62
Recap Clip 10.5: Inductive Logic Programming: An Example
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:07:44
63
Recap Clip 10.7: Inductive Logic Programming: Inverse Resolution
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:06:56
64
Recap Clip 11.1: Reinforcement Learning: Introduction & Motivation
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:04:29
Episode
Title
Lecturer
Updated
Via
Duration
Media
3
Lecture1. Admin/Overview
Prof. Dr. Michael Kohlhase
2021-04-13
Free
01:31:38
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
20.1.1. Sources of Uncertainty
Prof. Dr. Michael Kohlhase
2021-01-11
Free
00:07:35
2
20.1.2. Recap: Rational Agents as a Conceptual Framework
Prof. Dr. Michael Kohlhase
2021-01-11
Free
00:14:27
3
20.1.3. Agent Architectures based on Belief States
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:14:08
4
20.1.4. Modeling Uncertainty
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:28:00
5
20.1.5. Acting Under Uncertainty
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:11:56
6
20.1.6. Agenda for this Chapter: Basics of Probability Theory
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:01:56
7
20.2. Unconditional Probabilities (Part 1)
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:17:31
8
20.2. Unconditional Probabilities (Part 2)
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:23:25
9
20.3. Conditional Probabilities
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:07:55
10
20.4. Independence
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:17:28
11
20.5. Basic Probabilistic Reasoning Methods
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:22:22
12
20.6. Bayes' Rule
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:13:52
13
20.7. Conditional Independence
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:32:10
14
20.8. The Wumpus World Revisited
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:14:18
15
20.9. Conclusion
Prof. Dr. Michael Kohlhase
2021-01-28
Free
00:01:46
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
21.1. Introduction
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:04:10
2
21.2. What is a Bayesian Network?
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:22:47
3
21.3. What is the Meaning of a Bayesian Network?
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:15:22
4
21.4. Constructing Bayesian Networks (Part 1)
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:20:13
5
21.4. Constructing Bayesian Networks (Part 2)
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:26:48
6
21.5. Inference in Bayesian Networks
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:25:50
7
21.6. Conclusion
Prof. Dr. Michael Kohlhase
2021-02-01
Free
00:07:58
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
22.1. Introduction
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:17:29
2
22.2 Rational Preferences
Prof. Dr. Michael Kohlhase
2021-05-09
Free
00:12:36
3
22.3. Utilities and Money (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:14:04
4
22.3. Utilities and Money (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:16:57
5
22.4. Multi-Attribute Utility (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:29:12
6
22.4. Multi-Attribute Utility (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:14:42
7
22.5. Decision Networks
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:24:07
8
22.6. The Value of Information (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:17:01
9
22.6. The Value of Information (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:18:20
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
23.1 Time and Uncertainty
Prof. Dr. Michael Kohlhase
2021-05-10
Free
00:27:22
2
23.2. Inference: Filtering, Prediction and Smoothing (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:29:04
3
23.2. Inference: Filtering, Prediction and Smoothing (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:23:41
4
23.2. Inference: Filtering, Prediction and Smoothing (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:11:54
5
23.3. Hidden Markov Models (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:21:07
6
23.3. Hidden Markov Models (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:18:56
7
23.4. Dynamic Bayesian Networks
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:12:37
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
24. Making Complex Decisions
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:03:10
2
24.1. Sequential Decision Problems
Dr.-Ing. Dennis Müller
2021-03-29
Free
00:11:56
3
24.2. Utilities over Time
Dr.-Ing. Dennis Müller
2021-03-29
Free
00:21:54
4
24.3. Value/Policy Iteration
Dr.-Ing. Dennis Müller
2021-03-29
Free
00:21:05
5
24.4. Partially Observable MDPs
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:20:42
6
24.5. Online Agents with POMDPs
Prof. Dr. Michael Kohlhase
2021-03-29
Free
00:21:57
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
25. Learning from Observations
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:03:49
2
25.1. Forms of Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:20:26
3
25.2. Inductive Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:21:43
4
25.3. Learning Decision Trees
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:17:33
5
25.4. Using Information Theory (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:27:33
6
25.4. Using Information Theory (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:26:53
7
25.5. Evaluating and Choosing the Best Hypothesis (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:22:00
8
25.5. Evaluating and Choosing the Best Hypothesis (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:31:59
9
25.6. Computational Learning Theory (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:25:36
10
25.6. Computational Learning Theory (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:15:22
11
25.7. Regression and Classification with Linear Models (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:17:46
12
25.7. Regression and Classification with Linear Models (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:18:21
13
25.7. Regression and Classification with Linear Models (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:18:04
14
25.8. Artificial Neural Networks (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:19:21
15
25.8. Artificial Neural Networks (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:20:59
16
25.8. Artificial Neural Networks (Part 3)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:16:59
17
25.8. Artificial Neural Networks (Part 4)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:21:09
18
25.9. Support Vector Machines
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:28:28
19
Bonus: Science Slam
Jonas Betzendahl
2021-03-30
Free
00:12:41
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
26.1. Full Bayesian Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:13:26
2
26.2. Approximations of Bayesian Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:14:58
3
26.3. Parameter Learning for Bayesian Networks
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:17:25
4
26.4. Naive Bayes Models
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:11:19
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
27.1. Logical Formulations of Learning (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:20:00
2
27.1. Logical Formulations of Learning (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:21:38
3
27.2. Explanation-Based Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:32:40
4
27.3. Relevance-Based Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:26:56
5
27.4.1. Inductive Logic Programming: An Example
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:07:40
6
27.4.2. Inductive Logic Programming: Top-Down Inductive Learning: FOIL
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:18:48
7
27.4.3. Inductive Logic Programming: Inverse Resolution
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:21:22
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
28.1. Reinforcement Learning: Introduction & Motivation
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:11:14
2
28.2. Passive Learning
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:10:46
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
29.1 Introduction to NLP
Prof. Dr. Michael Kohlhase
2021-07-03
Free
00:16:16
2
29.2 Natural Language and its Meaning
Prof. Dr. Michael Kohlhase
2021-07-03
Free
00:24:57
3
29.3 Looking at Natural Language
Prof. Dr. Michael Kohlhase
2021-07-03
Free
00:28:16
4
29.4 Language Models
Prof. Dr. Michael Kohlhase
2021-07-01
Free
00:25:30
5
29.5 Information Retrieval
Prof. Dr. Michael Kohlhase
2021-07-02
Free
00:18:56
6
29.6 Word Embeddings
Prof. Dr. Michael Kohlhase
2021-07-02
Free
00:15:37
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
27.1 Communication Phenomena
Prof. Dr. Michael Kohlhase
2021-07-09
Free
00:13:57
2
30.2 Grammars and Syntactic Processing
Prof. Dr. Michael Kohlhase
2021-07-09
Free
00:45:55
3
30.3 Real Language Phenomena
Prof. Dr. Michael Kohlhase
2021-07-09
Free
00:14:39
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
31. What did we learn in AI 1/2? (Part 1)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:27:11
2
31. What did we learn in AI 1/2? (Part 2)
Prof. Dr. Michael Kohlhase
2021-03-30
Free
00:19:14

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