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...
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...
The CO2 costs of video streaming
The Covid-19 crisis pushed many of us to change our working styles. As universities all over Germany changed to an online version, video streaming became a daily necessecity for students to follow the lectures and for professor to be able to evaluate the students' presentations. We hear very often that the stay-home orders amend Covid-19...
Free download of our ASOC Article until November, 02, 2017
If you are interested in our recent article Self-adjusting parameter control for surrogate-assisted constrained optimization under limited budgets which appeared in the journal Applied Soft Computing (ASOC), please take the opportunity to follow this link: https://authors.elsevier.com/a/1Vj555aecSVnxb. For a period until November, 02, 2017, this link will provide the free download of the final journal article....
Samineh Bagheri Wins Best Student Paper Award
We are happy to announce that Samineh Bagheri has won the Best Student Paper Award at "IEEE Symposium Series on Computational Intelligence" (IEEE SSCI 2016), a conference held in Athens, Greece . Read more here ...
"Online Selection of Surrogate Models for Constrained Black-Box Optimization" to be presented at SSCI 2016
We are delighted to announce that our recent research work related to online model selection for constrained optimization has been accepted for publication and it will be presented at SSCI 2016. The SSCI 2016 conference will be held in Athens, Greece, from 6th to 9th of December, 2016. Many plenary and keynote talks are planned in the wide...
New Technical Report on Temporal Difference Learning for Games
A new technical report on temporal difference (TD) learning for games and "self-play" algorithms for game-agent training is available. This report by Wolfgang Konen features a gentle introduction to TD learning for game play and gives hints for the practioner on the implementation of such algorithms . It shows the references to the most recent...
A New Repair Method For Constrained Optimization
Many real-world optimization problems are dealing with constraints. The valid solution for constrained optimization problems (COP) lies somewhere in the feasible region which is a sub-set of the input-space. The borders of the feasible area are defined by one or many constraints. Existance of constraints makes the optimization problems more demanding. There are different approaches to...