A Virtual Maze Game to Explain Reinforcement Learning
| Autor: | Youri Coppens, Eugenio Bargiacchi, Ann Nowe |
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| Přispěvatelé: | Beuls, Katrien, Bogaerts, Bart, Bontempi, Gianluca, Geurts, Pierre, Harley, Nick, Lebichot, Bertrand, Lenaerts, Tom, Louppe, Gilles, Van Eecke, Paul, Informatics and Applied Informatics, Faculty of Sciences and Bioengineering Sciences, Artificial Intelligence, Computational Modelling |
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| Zdroj: | Vrije Universiteit Brussel Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019): Proceedings of the Reference AI & ML Conference for Belgium, Netherlands & LuxemburgProceedings of the Reference AI & ML Conference for Belgium, Netherlands & Luxemburg. CEUR Workshop Proceedings |
| Popis: | We demonstrate how Virtual Reality can explain the basic concepts of Reinforcement Learning through an interactive maze game. A player takes the role of an autonomous learning agent and must learn the shortest path to a hidden treasure through experience. This application visualises the learning process of Watkins' Q(λ), one of the fundamental algorithms in the field. A video can be found at https://youtu.be/sLJRiUBhQqM. info:eu-repo/semantics/published |
| Databáze: | OpenAIRE |
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