Matching Games and Algorithms for General Video Game Playing

Authors

  • Philip Bontrager New York University
  • Ahmed Khalifa New York University
  • Andre Mendes New York University
  • Julian Togelius New York University

DOI:

https://doi.org/10.1609/aiide.v12i1.12884

Keywords:

clustering, video game description language, general video game playing, AI, algorithm selection

Abstract

This paper examines the performance of a number of AI agents on the games included in the General Video Game Playing Competition. Through analyzing these results, the paper seeks to provide insight into the strengths and weaknesses of the current generation of video game playing algorithms. The paper also provides an analysis of the given games in terms of inherent features which define the different games. Finally, the game features are matched with AI agents, based on performance, in order to demonstrate a plausible case for algorithm portfolios as a general video game playing technique.

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Published

2021-06-25

How to Cite

Bontrager, P., Khalifa, A., Mendes, A., & Togelius, J. (2021). Matching Games and Algorithms for General Video Game Playing. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 12(1), 122-128. https://doi.org/10.1609/aiide.v12i1.12884