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 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...

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,

New Technical Report on Temporal Difference Learning for Games

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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...