Game Datasets

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In computer science, Artificial Intelligence (AI) is intelligence demonstrated by machines. Its definition, AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that achieving its goals Russell et. al (2016).

Withal, Data Mining (DM) is the process of discovering patterns in data sets (or datasets) involving methods of machine learning, statistics, and database systems; DM focus on extract the information of datasets Han (2011).

This repository serves as a guide for anyone who wants to work with Artificial Intelligence or Data Mining applied in digital games! Here you will find a series of datasets, tools and materials available to build your application or dataset.


Any suggestions or doubts, please open an "issue". If you want to contribute, read this and make a "pull request".


API is "a set of functions and procedures allowing the creation of applications that access the features or data of an operating system, application, or other service" (Google).

Artificial Intelligence




Market Research



  • Drachen, A. Mirza-Babaei, P. Nacke, L. (2018). Games user research. Oxford.
  • El-Nasr, S. Drachen, A. Canossa, A. (2013). Game analytics: maximizing the value of player data. Sprigner.
  • Han, J., Pei, J., Kamber, M. (2011). Data mining: concepts and techniques. Elsevier.
  • Hennig-Thurau, T. Houston, M. (2018). Entertainment science: data analytics and practical theory for movies, games, music and books. Springer.
  • Loh, A. Sheng, Y. Ifenthaler, D. (2015). Serious games analytics: methodologies for performance measurement, assessment, and improvement. Springer.
  • Russell, S. J., Norvig, P. (2016). Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited.
  • Yannakakis, G. N., Togelius, J. (2018). Artificial intelligence and games. Springer.


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