Techniques in Artificial Intelligence (IN2062)
Course 240927786 in WS 2018/9
General Data
| Course Type | lecture with integrated exercises |
|---|---|
| Semester Weekly Hours | 4 SWS |
| Organisational Unit | Informatics 6 - Chair of Robotics, Artificial Intelligence and Real-time Systems (Prof. Knoll) |
| Lecturers |
Matthias Althoff |
| Dates |
Wed, 14:00–16:00, MI HS1 Fri, 13:00–14:30, MW 2001 Wed, 11:00–12:00, MI 03.07.023 and 2 singular or moved dates |
Assignment to Modules
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IN2062: Grundlagen der Künstlichen Intelligenz / Techniques in Artificial Intelligence
This module is included in the following catalogs:- Focus Area Imaging in M.Sc. Biomedical Engineering and Medical Physics
- Catalogue of non-physics elective courses
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks | - Task environments and the structure of intelligent agents. - Solving problems by searching: breadth-first search, uniform-cost search, depth-first search, depth-limited search, iterative deepening search, greedy best-first search, A* search. - Constraint satisfaction problems: defining constraint satisfaction problems, backtracking search for constraint satisfaction problems, heuristics for backtracking search, interleaving search and inference, the structure of constraint satisfaction problems. - Logical agents: propositional logic, propositional theorem proving, syntax and semantics of first-order logic, using first-order logic, knowledge engineering in first-order logic, reducing first-order inference to propositional inference, unification and lifting, forward chaining, backward chaining, resolution. - Bayesian networks: acting under uncertainty, basics of probability theory, Bayesian networks, inference in Bayesian networks, approximate inference in Bayesian networks. - Hidden Markov models: time and uncertainty, inference in hidden Markov models (filtering, prediction, smoothing, most likely explanation), approximate inference in hidden Markov models. - Rational decisions: introduction to utility theory, utility functions, decision networks, the value of information, Markov decision processes, value iteration, policy iteration, partially observable Markov decision processes. - Learning: types of learning, supervised learning, learning decision trees. - Introduction to robotics: robot hardware, robotic perception, path planning, planning uncertain movements, control of movements, robotic software architectures, application domains. |
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| Links |
Course documents E-Learning course (e. g. Moodle) Additional information TUMonline entry |
Equivalent Courses (e. g. in other semesters)
| Semester | Title | Lecturers | Dates |
|---|---|---|---|
| WS 2023/4 | Techniques in Artificial Intelligence (IN2062) | Althoff, M. Külz, J. Lercher, F. Lützow, L. Mair, S. |
Thu, 16:00–18:00, MW 0001 Fri, 13:00–14:30, MW 2001 and singular or moved dates |
| WS 2022/3 | Techniques in Artificial Intelligence (IN2062) | Althoff, M. Gaßner, J. Kulmburg, A. Meyer, E. Würsching, G. |
Thu, 16:00–18:00, MW 0001 Fri, 13:00–14:30, MW 2001 and singular or moved dates |
| WS 2021/2 | Techniques in Artificial Intelligence (IN2062) | Althoff, M. Gaßner, J. Kulmburg, A. Meyer, E. Würsching, G. |
Thu, 16:00–18:00, MW 0001 Fri, 13:00–14:30, MW 2001 |
| WS 2020/1 | Techniques in Artificial Intelligence (IN2062) | Althoff, M. Klischat, M. Mayer, M. Wang, X. |
Thu, 16:00–18:00, virtuell Fri, 13:00–14:30, virtuell Wed, 10:00–12:00, virtuell Thu, 16:00–18:00, virtuell |
| WS 2019/20 | Techniques in Artificial Intelligence (IN2062) | Althoff, M. Klischat, M. Maierhofer, S. Wang, X. |
Thu, 16:00–18:00, MW 0001 Fri, 13:00–14:30, MW 2001 Wed, 10:00–12:00, MI 03.13.010 |
| WS 2017/8 | Techniques in Artificial Intelligence (IN2062) | Althoff, M. |
Wed, 14:00–16:00, MI HS1 Fri, 12:45–14:15, MW 0001 and singular or moved dates |
| WS 2016/7 | Techniques in Artificial Intelligence (IN2062) | Althoff, M. |
Wed, 14:00–16:00, MI HS1 Fri, 12:45–14:15, MW 0001 |
| WS 2015/6 | Techniques in Artificial Intelligence (IN2062) |
Wed, 14:00–16:00, MI HS1 Fri, 12:00–14:00, Interims I 101 and singular or moved dates |
|
| WS 2014/5 | Techniques in Artificial Intelligence (IN2062) |
Thu, 16:00–18:00, Interims I 101 Fri, 12:00–14:00, Interims I 101 and singular or moved dates |
|
| WS 2013/4 | Techniques in Artificial Intelligence (IN2062) |
Thu, 16:00–18:00, Interims I 101 Fri, 12:00–14:00, Interims I 101 and singular or moved dates |
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| WS 2012/3 | Techniques in Artificial Intelligence (IN2062) |