In the last week of February, my RL3 Dataninja colleague Moritz Lange and I had the chance to visit the AAAI conference on AI 2024. Listening to Yann LeCun in person speak about the challenges of machine learning was inspiring and attending Moritz' presentation of our collaborative work "Interpretable Brain-Inspired Representations Improve RL Performance on...
Dataninja Retreat 2023
From September 6th to September 9th we held our last annual retreat of the Dataninja research training group in Krefeld. Alongside our invited speaker's talk (Dr. Alessandro Fabris from Max Planck Institute for Security and Privacy) about algorithmic fairness, each PhD candidate from the Dataninja projects presented their progress and current investigations. In my contribution...
Two papers accepted for our second participation at LOD 2023 conference
For the second time we (Raphael Engelhardt and Wolfgang Konen) have been given the opportunity to present our work at the Conference on machine Learning, Optimization and Data science (LOD) conference. To this year's 9th edition, held in Grasmere, England, UK on September 22nd - 26th we have the honor to contribute even two papers...
Article Published in Special Issue of "Algorithms"
We are delighted to announce that our article “Iterative Oblique Decision Trees Deliver Explainable RL Models” was accepted and is now part of the special issue “Advancements in Reinforcement Learning Algorithms” in the MDPI journal Algorithms (impact factor 2.2, CiteScore 3.7) . Explainability in AI and RL (known as XAI and XRL) becomes increasingly important....
Dataninja Spring-School 2023
The second edition of the Dataninja Spring-School was held from 8th to 10th of May 2023 in Bielefeld and as a hybrid event. We had the honor and pleasure to attend talks and tutorials from renowned researchers and aspiring young scientists. We contributed with an extended abstract and our scientific poster “Finding the Relevant Samples...
AI in Nuclear Power Plant Simulation: Steinmüller Engineering Award for Niklas Fabig
The operation of nuclear power plants (NPPs) is one of the most safety-critical tasks in industry. Prior to using AI methods in this area, it should be thoroughly investigated and evaluated via simulations, whether AI can learn (e.g.´, by reinforcment learning, RL) to power up and shut down a nuclear reactor and how well such...
Presenting our Approach to Explainable Reinforcement Learning at LOD 2022 Conference
As previously announced, last week I had the pleasure to present our joint work with our partners from Ruhr-University Bochum on explainable reinforcement learning at the 8th Annual Conference on machine Learning, Optimization and Data science (LOD). The presentation sparked interesting questions and lead to inspiring discussions in the enchanting ambiance of the medieval monastery...
Dataninja Retreat 2022
The second edition of the annual Dataninja-Retreat took place this September in Tecklenburg. The different Dataninja projects presented their proceedings, we had the pleasure of attending a lecture by Prof. Xiaoyi Jiang, and fresh PhD graduates of the KI-Starter-project kindly shared experiences and some tips from their recently concluded PhD-journey. Last but not least it...
Researchers from TH Köln present at international conference LOD 2022
We are pleased to announce that we will present our research on explainable reinforcement learning at the 8th Annual Conference on machine Learning, Optimization and Data science (LOD). Starting with its first edition in 2015, the LOD is an established international and interdisciplinary forum for research and discussion of Deep Learning, Optimization, Big Data, and...
Presenting our Work at KI 2021
In September 2021, shortly after the Dataninja retreat, we participated at the KI 2021 – 44th German Conference on Artificial Intelligence. Alongside fellow members of the Dataninja research training group we, Raphael Engelhardt and Wolfgang Konen from TH Köln together with Laurenz Wiskott and Moritz Lange from RUB Bochum, presented our work on rule extraction...