Bibliograph.
Daten | Bock, Pascal: Development of a benchmarking framework for Inverse Reinforcement Learning algorithms based on Tetris.
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik, Studienarbeit Nr. 2464 (2015).
38 Seiten, englisch.
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| CR-Klassif. | D.2.8 (Software Engineering Metrics)
H.5.2 (Information Interfaces and Presentation User Interfaces)
I.2.1 (Applications and Expert Systems)
I.2.6 (Artificial Intelligence Learning)
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| Kurzfassung | Tetris is one of the oldest, most popular and most well-known video games. The simple rules and scoring options make it a viable choice for benchmarking artificial intelligence, especially in the machine learning department. This work describes a customizable benchmarking frame- work using a simplified variant of the original Tetris game focused on Inverse Reinforcement Learning algorithms.
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Volltext und
andere Links | PDF (243333 Bytes)
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| Abteilung(en) | Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Maschinelles Lernen und Robotik
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| Betreuer | Toussaint, Marc |
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| Eingabedatum | 20. April 2015 |
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