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...

Posts nach Kategorien: Reinforcement Learning

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 in Game learning research area which is a very interesting sub-field of artifical intelligence. In 2018,

Posts nach Kategorien: Reinforcement Learning

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...

Posts nach Kategorien: Reinforcement Learning

Prize for CIOP Bachelor Thesis in Reinforcement Learning

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Mr. Markus Thill has won the first price in the 2012 OPITZ CONSULTING “Innovation in Informatics” contest. Many congratulations from the CIOP team!! Mr. Thill’s thesis advanced the state of the art in reinforcement learning for complex board games, here Connect Four. Read more about his work on this page. 

Posts nach Kategorien: Reinforcement Learning