Researchers from TH Köln present at international conference LOD2022

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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

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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...

Dataninja Retreat 2021

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Between the third and fourth wave of the COVID-19 pandemic, we were in September 2021 lucky enough to hold in presence the annual retreat of the Dataninja research group, which was at the same time the group's first ever in-person meeting. The rich and balanced program included presentations of the different Dataninja projects by the...

More Transparency in Artificial Intelligence

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(Image: Christoph J Kellner)   For the research project (RL)^3, which is lead by Laurenz Wiskott (RUB) and Wolfgang Konen (TH Köln) and that is illustrated in the figure above, there is now a press release TH Köln available:  https://www.th-koeln.de/hochschule/mehr-transparenz-bei-kuenstlicher-intelligenz_84905.php (sorry, in German only!). (RL)^3 is part of the graduate school Dataninja (Trustworthy AI for Seamless...

Dataninja.nrw Inauguration on May, 3rd, 16:00

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We are happy to announce the dataninja.nrw inauguration event that takes place virtually on Monday, May, 3rd, 16-18. Our research group (RL)^3 at TH Köln is part of the AI graduate school dataninja.nrw with a PhD tandem together with Ruhr University Bochum. Please see the attached PDF dataninja_inauguration_05_03 for all the details and the programme of...

Deep Learning and Reinforcement Learning at BIOMA'2020

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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...

TH Köln takes part in AI Graduate College Data-NInJA

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The State of North Rhine-Westphalia provides a grant for the AI Graduate College Data-NInJA („Trustworthy AI for Seamless Problem Solving: Next Generation Intelligence Joins Robust Data Analysis“), coordinated by Prof. Barbara Hammer, University Bielefeld. The grant consists of seven PhD tandems, which were selected out of 37 applications for this grant by an expert jury. TH...

TH Köln presents at IEEE CONFERENCE ON GAMES (CoG) 2019, London, UK

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   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...

Deep Learning and Reinforcement Learning Summer School

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The deep learning and reinforcement learning summer schools hosted by Canadian Institute For Advanced Research (CIFAR) and the Vector Institute are among the most prestigious summer schools in the field of machine learning and artificial intelligence. This year the summer school was taking place in Toronto, Canada from 25th of July till 3rd of August...

General Board Game Playing as Educational Tool

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GBG (General Board Game Playing & Learning) is an Open Source software framework developed at TH Köln, University of Applied Sciences. GBG aims to ease the entry for the students into game learning and the reinforcement learning research area which is a very interesting sub-field of artifical intelligence. In 2018,