Studienarbeit STUD-2464

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.
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)
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.

Volltext und
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PDF (243333 Bytes)
Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Maschinelles Lernen und Robotik
BetreuerToussaint, Marc
Eingabedatum20. April 2015
   Publ. Informatik