Algorithms for Decision Making

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

Enrollment:

https://moodle.ruhr-uni-bochum.de/course/view.php?id=60664
There might still be places available. Please contact robert.schmidt@rub.de if you would like to take part.

Examination:
Oral presentation

Lecturers

Details

Course type
Seminars
Credits
3
Term
Winter Term 2024/2025
E-Learning
moodle course available

Dates

Seminar
Takes place every week on Tuesday from 16:00 to 18:00 in room IC 03/447.
First appointment is on 08.10.2024
Last appointment is on 28.01.2025

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

About the INI

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through 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 approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Contact

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210

sekretariat@ini.rub.de
www.ini.rub.de