A curated list of awesome game datasets, and tools to artificial intelligence in games

Overview

🎮 Awesome Game Datasets Awesome

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.

Contributing

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


Contents


API

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

Mobile

Web


Books

  • 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.

Dataset

Related


Market Research


Miscellaneous


License

Creative Commons License

Owner
Leonardo Mauro
Data Scientist | Professor (Data Mining, Machine Learning, Business Intelligence).
Leonardo Mauro
MVSDF - Learning Signed Distance Field for Multi-view Surface Reconstruction

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110 Dec 20, 2022
Local Multi-Head Channel Self-Attention for FER2013

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A variational Bayesian method for similarity learning in non-rigid image registration (CVPR 2022)

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daniel grzech 14 Nov 21, 2022
“Data Augmentation for Cross-Domain Named Entity Recognition” (EMNLP 2021)

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<a href=[email protected]"> 18 Sep 10, 2022
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22)

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Shigang Li 9 Oct 29, 2022
Attention mechanism with MNIST dataset

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YeongHyeon Park 12 Jun 10, 2022
Kohei's 5th place solution for xview3 challenge

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Official implementation of "Learning Forward Dynamics Model and Informed Trajectory Sampler for Safe Quadruped Navigation" (RSS 2022)

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Dense matching library based on PyTorch

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Prune Truong 399 Dec 28, 2022
Video Frame Interpolation without Temporal Priors (a general method for blurry video interpolation)

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PyTorch code for ICPR 2020 paper Future Urban Scene Generation Through Vehicle Synthesis

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Stacked Recurrent Hourglass Network for Stereo Matching

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Gapmm2: gapped alignment using minimap2 (align transcripts to genome)

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linhua 326 Nov 22, 2022
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

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152 Jan 02, 2023
Reinforcement learning for self-driving in a 3D simulation

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Collection of in-progress libraries for entity neural networks.

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[内测中]前向式Python环境快捷封装工具,快速将Python打包为EXE并添加CUDA、NoAVX等支持。

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SiT: Self-supervised vIsion Transformer

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Sara Ahmed 275 Dec 28, 2022
Official implementation of VQ-Diffusion

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