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Title: Matching games and algorithms for general video game playing
Authors: Bontrager, Philip
Khalifa, Ahmed
Mendes, Andre
Togelius, Julian
Keywords: Computer games
Artificial intelligence
Machine learning
Issue Date: 2016
Publisher: Association for the Advancement of Artificial Intelligence
Citation: Bontrager. P., Khalifa, A., Mendes, A., & Togelius, J. (2016). Matching games and algorithms for general video game playing. The Twelfth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE-16), Burlingame. 122-128.
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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