Machine Learning with the Pong Game: A Case Study

被引：3

作者：

Nork, Benedikt ^{[1
]}

Lengert, Geraldine Denise ^{[1
]}

Litschel, Robert Uwe ^{[1
]}

Ahmad, Nasim ^{[1
]}

Lam, Gia Thuan ^{[2
]}

Logofatu, Doina ^{[1
]}

机构：

[1] Frankfurt Univ Appl Sci, Dept Comp Sci & Engn, D-60318 Frankfurt, Germany

[2] Vietnamese German Univ, Le Lai St, Thu Dau Mot City, Vietnam

来源：

ENGINEERING APPLICATIONS OF NEURAL NETWORKS, EANN 2018 | 2018年 / 893卷

关键词：

Pong game; Machine Learning; Self-playing agent;

D O I：

10.1007/978-3-319-98204-5_9

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Being one of the earliest computer games, the Pong game is well-known for its simplicity, which makes it suitable for becoming one of the very first problems in Artificial Intelligence and Machine Learning: The goal is to create a self-playing agent that can compete against humans. In the past there have been introduced various Machine Learning approaches to solve this problem. This paper gives a summary of some notable techniques to creating a self-learning agent for the Pong game. In addition, it proposes a template for developing this idea into a full-fledged application. An implementation in Java is available online.

引用

页码：106 / 117

页数：12

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