Techniques in Artificial Intelligence
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
Module version of SS 2015 (current)
There are historic module descriptions of this module. A module description is valid until replaced by a newer one.
Whether the module’s courses are offered during a specific semester is listed in the section Courses, Learning and Teaching Methods and Literature below.
|available module versions|
|SS 2015||WS 2011/2|
IN2062 is a semester module in German or English language at Bachelor’s level and Master’s level which is offered in winter semester.
This Module is included in the following catalogues within the study programs in physics.
- Focus Area Imaging in M.Sc. Biomedical Engineering and Medical Physics
- Catalogue of non-physics elective courses
|Total workload||Contact hours||Credits (ECTS)|
|150 h||60 h||5 CP|
Content, Learning Outcome and Preconditions
- design principles and specification mechanisms for rational agents;
- problem solving using heuristic search: heuristic search techniques, optimizing search;
- problem solving using knowledge-based techniques: logic and inference techniques; reasoning about space and time; representation of ontologies; representation and reasoniong in the common sense world;
- problem solving using uncertain knowledge and information: basic concepts of probability and decision theory; Bayesian Networks; planning with Markov decision problems;
- action planning: automatic generation of partially ordered action plans; planning and execution;
- machine learning: learning decision trees; inductive learning; probably approximately correct learning; reinforcement learning.
Examples are search algorithms, methods of logical inference, as well as computation of state probabilities of Bayesian networks and hidden Markov models.
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
|VI||4||Techniques in Artificial Intelligence (IN2062)||Althoff, M. Gaßner, J. Kulmburg, A. Meyer, E. Würsching, G.||
Fri, 13:00–14:30, MW 2001
Thu, 16:00–18:00, MW 0001
Learning and Teaching Methods
Description of exams and course work
A collection of formulas and tables required to solve the given problems is provided. Students are only allowed to bring pens and a calculator (non-progammable). The questions require to solve problems mathematically and to answer questions in natural language.
The exam may be repeated at the end of the semester.