Decision Making under Risk and Uncertainty
Event details
| Date | 08.06.2026 |
| Hour | 10:00 › 12:00 |
| Speaker | Bo-Yu Yang |
| Location | |
| Category | Conferences - Seminars |
EDIC candidacy exam
Exam president: Prof. Emre Telatar
Thesis advisor: Prof. Michael Gastpar
Co-examiner: Prof. Negar Kiyavash
Abstract
In real-world decision problems, human needs can differ widely in background, culture, and objectives, making it difficult to design a single universal value function for agents. To design a model dealing with specific tasks, a natural starting point is to specify an appropriate utility (reward) function and optimize it. However, in practice, there are many factors that require attention when making decisions. This work mainly considers two factors: risk and uncertainty, and aims to study decision making through an information-theoretic lens, developing algorithms and interpretations for optimizing risk-sensitive utility functions under uncertainty.
Selected papers
coming soon
Exam president: Prof. Emre Telatar
Thesis advisor: Prof. Michael Gastpar
Co-examiner: Prof. Negar Kiyavash
Abstract
In real-world decision problems, human needs can differ widely in background, culture, and objectives, making it difficult to design a single universal value function for agents. To design a model dealing with specific tasks, a natural starting point is to specify an appropriate utility (reward) function and optimize it. However, in practice, there are many factors that require attention when making decisions. This work mainly considers two factors: risk and uncertainty, and aims to study decision making through an information-theoretic lens, developing algorithms and interpretations for optimizing risk-sensitive utility functions under uncertainty.
Selected papers
coming soon
Practical information
- General public
- Free