After having participated in its debut last year, it was a special pleasure to visit the second edition of The World Conference on Explainable Artificial Intelligence (xAI2024). The conference was a full immersion into all aspects of explainable AI. The keynote speech by Prof. Fosca Giannotti about hybrid decision-making and the two panel discussions on...
Visiting the AAAI Conference on Artificial Intelligence in Vancouver
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-Tandem wins Best Paper Award at LOD 2023 conference
Our participation in this year's edition of the LOD conference, as previously announced in one of our blog post, proved to be an exceptionally enjoyable experience. The systematic evaluation of auxiliary tasks in reinforcement learning published in “Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-Visual Environments: A Comparison” by first author Moritz Lange (Dataninja-colleague...
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....
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...
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...
Deep Learning and Reinforcement Learning at BIOMA'2020
We are happy to announce that the CIOP group of TH Köln participated with two papers and two talks at the 9th International Conference BIOMA'2020 (Bioinspired Optimization Methods and Applications), which took place November 2020, 19th-20th, and was this year a completely online event: "Reinforcement Learning for N-Player Games: The Importance of Final Adaptation" by...
PhD Candidate from CIOP Group Wins Best Paper Award
Electrocardiogram with Anomalies Markus Thill, who is PhD student in our CIOP group, is working on developing new anomaly detection algorithms since 2017 under supervision of Prof. Wolfgang Konen. The field of anomaly detection, which is today often tackled with machine learning algorithms, became a hot topic in the last years. Thill's recent paper titled...
TH Köln presents at IEEE CONFERENCE ON GAMES (CoG) 2019, London, UK
Wolfgang Konen presented his work on General Board Game Playing at CoG'2019, the Conference on Games, which took place between 20-23 of August in London, UK. You can find the poster here and the accompanying paper here on arXiv. The General Board Game (GBG) Playing Framework is about computer agents that learn game strategies...