Abstract
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.
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Nork, B., Lengert, G.D., Litschel, R.U., Ahmad, N., Lam, G.T., Logofătu, D. (2018). Machine Learning with the Pong Game: A Case Study. In: Pimenidis, E., Jayne, C. (eds) Engineering Applications of Neural Networks. EANN 2018. Communications in Computer and Information Science, vol 893. Springer, Cham. https://doi.org/10.1007/978-3-319-98204-5_9
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DOI: https://doi.org/10.1007/978-3-319-98204-5_9
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