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| Semester | spring semester 2024 |
| Course frequency | Every spring sem. |
| Lecturers | Malte Helmert (malte.helmert@unibas.ch, Assessor) |
| Content | The course offers an introduction into the basic concepts, problems, methods and algorithms of artificial intelligence. Topics include: introduction and historical development of AI, rational agents and their environments, state-space search, combinatorial optimization, constraint satisfaction problems, formal logic, automated planning, and board games. |
| Learning objectives | Students learn the theoretical and practical foundations of classical problems in artificial intelligence and their algorithmic solution. In particular, participants will obtain the necessary knowledge and skills to independently solve typical AI problems by selecting, implementing and evaluating standard algorithms from the AI literature. |
| Bibliography | Stuart Russell and Peter Norvig: Artificial Intelligence - A Modern Approach (4th edition), Prentice Hall, 2020. |
| Weblink | course web page |
| Admission requirements | No formal requirements, but solid basic knowledge of foundational concepts in computer science (algorithms, complexity theory) and mathematics (formal proofs and basic concepts like sets, functions and relations) are necessary for following the lecture. Good programming skills are necessary for some of the exercises. |
| Course application | https://services.unibas.ch/ |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Course auditors welcome |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| wöchentlich | Monday | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| wöchentlich | Wednesday | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Date | Time | Room |
|---|---|---|
| Monday 26.02.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 28.02.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 04.03.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 06.03.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 11.03.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 13.03.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 18.03.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 20.03.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 25.03.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 27.03.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 01.04.2024 | 16.15-18.00 | Ostern |
| Wednesday 03.04.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 08.04.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 10.04.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 15.04.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 17.04.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 22.04.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 24.04.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 29.04.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 01.05.2024 | 14.15-16.00 | Tag der Arbeit |
| Monday 06.05.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 08.05.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 13.05.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 15.05.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 20.05.2024 | 16.15-18.00 | Pfingstmontag |
| Wednesday 22.05.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Monday 27.05.2024 | 16.15-18.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 29.05.2024 | 14.15-16.00 | Biozentrum, Hörsaal U1.141 |
| Wednesday 03.07.2024 | 14.00-16.00 | Biozentrum, Hörsaal U1.131 |
| Modules |
Modul: Applications and Related Topics (Bachelor's degree subject: Computer Science) Modul: Computational Methods (Bachelor's Studies: Computational Sciences) Modul: Computational Methods (Bachelor's Studies: Computational Sciences) Modul: Computational Methods (Bachelor's Studies: Computational Sciences) Modul: Computational Methods (Bachelor's Studies: Computational Sciences) Modul: Computational Methods (Bachelor's Studies: Computational Sciences) Module: Computational Sciences II (Bachelor's Studies: Computational Sciences (Start of studies before 01.08.2023)) Module: Machine Intelligence (Bachelor's Studies: Computer Science) Module: Machine Learning Foundations (Master's Studies: Data Science) |
| Assessment format | continuous assessment |
| Assessment details | The course includes weekly homework assignments and weekly exercise sessions. To pass the course, students need to successfully work on the homework assignments and pass the final written examination. At least 50% of the possible marks from homework assignment are needed to qualify for the final exam. The final grade for the course is based exclusively on the final exam, which will take place as a written exam. Expected date of the exam: Wednesday, July 3, 2-4 p.m.. |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,5 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Science, studiendekanat-philnat@unibas.ch |
| Offered by | Fachbereich Informatik |