3 papers
cs.AI2024
Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming
Manuel Eberhardinger, Florian Rupp, Johannes Maucher +1
Despite tremendous progress, machine learning and deep learning still suffer from incomprehensible predictions. Incomprehensibility, however, is not an option for the use of (deep)…
cs.CV2024
Classification of Inkjet Printers based on Droplet Statistics
Patrick Takenaka, Manuel Eberhardinger, Daniel Grießhaber +1
Knowing the printer model used to print a given document may provide a crucial lead towards identifying counterfeits or conversely verifying the validity of a real document. Inkjet…
cs.AI2023
Learning of Generalizable and Interpretable Knowledge in Grid-Based Reinforcement Learning Environments
Manuel Eberhardinger, Johannes Maucher, Setareh Maghsudi
Understanding the interactions of agents trained with deep reinforcement learning is crucial for deploying agents in games or the real world. In the former, unreasonable actions co…