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- Algorithms for Decision Making
Algorithms for Decision Making
From the 1st of August to the 1st of September 2025 interested students can apply for a place in the seminar. The allocation of places will take place via the following central Moodle course of the faculty: https://moodle.ruhr-uni-bochum.de/course/view.php?id=62179.
The final allocation of places will take place by the 15th of September 2025 at the latest. Complete your binding registration by registering for the seminar via FlexNow. Please note that following the above steps is mandatory. Enrolment via FlexNow without prior registration via the central Moodle course is not permitted.
Content:
Automated decision-making systems are used for many important problems in engineering (e.g. automated driving), medicine (e.g. cancer screening), economics (e.g. portfolio allocation), environmental science (wildfire surveillance), and space travel (e.g. Mars exploration). In their recent book [1], Kochenderfer et al. examine different decision-making algorithms from a computational perspective, with a focus on the problem of uncertainty. Uncertainty can be represented using probability distributions and can occur on different levels, such as uncertainty about the outcome of actions or about the underlying world model.
Overall, the different parts of the book cover Probabilistic Reasoning, Sequential Problems, Model Uncertainty, State Uncertainty, and Multiagent Systems. Each part of the book contains then several chapters with a more specific topic describing mathematical problem formulations and computational approaches, often closely related to reinforcement learning and planning.
Each student will cover the topic from a book chapter in a presentation in the seminar, followed by a discussion of the topic with active participation from the whole seminar group.
Max. number of participants: 20
Learning Outcomes:
• Knowledge on different algorithms and computational approaches for decision making
• Explain the underlying mathematical problem formulations and the implementation of the algorithms to solve them
• Insight into different types of uncertainty and the balancing of multiple objectives
• Discuss practical applications of the theoretical frameworks
• Present the algorithms and mathematical problem formulations to an audience
Examination:
Oral presentation
Lecturers
![]() Prof. Dr. Robert SchmidtLecturer |
(+49) 234-32-27300 robert.schmidt@rub.de NB 3/68 |
Details
- Course type
- Seminars
- Credits
- 3
- Term
- Winter Term 2025/2026
- E-Learning
- moodle course available
Dates
- Seminar
-
Takes place
every week on Monday from 16:00 to 18:00.
First appointment is on 13.10.2025
Last appointment is on 02.02.2026
Requirements
Knowledge of calculus, linear algebra, and probability concepts. Background in artificial intelligence, e.g. via the course “Introduction to Artificial Intelligence”.
Literature: Kochenderfer, M. J., Wheeler, T. A., & Wray, K. H. (2022). Algorithms for decision making. MIT press. https://algorithmsbook.com/files/dm.pdf
The Institut für Neuroinformatik (INI) is a research unit of the Faculty of Computer Science at the Ruhr-Universität Bochum. Its scientific goal is to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental psychology and neurophysiology as well as machine learning, neural artificial intelligence, computer vision, and robotics.
Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany
Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210