Reinforcement Learning Analysis Framework
Description
The aim of this project is to implement a framework that facilitates the development of RL solutions for real-world applications. This is necessary since the academic literature usually focuses on specific algorithms and approaches differ widely for different regions in the highly complex RL problem space. Especially, we systematically study the effectiveness of different RL approaches in the context of different simulation models.
Key Data
Projectlead
Dr. Claus Horn
Deputy Projectlead
Project status
completed, 01/2022 - 12/2022
Funding partner
Internal
Project budget
40'000 CHF