VGLC Examples

Some introductory-level machine learning projects that make use of the Video Game Level Corpus.

Usage

The Video Game Level Corpus used for these examples can be found here.

The entire corpus should be contained in the folder called "VGLC", and the Python files should be run in the same directory as the "VGLC" folder.

Three example projects are included - each within a separate Python file:

vglc_k_means.py: Splits a set of levels into tiles and attempts to cluster the tiles into levels based on tile structure (occupied vs. non-occupied spaces). A separate file is generated for each cluster, named k_means_<cluster_num>.txt, which contains the centroid as the first entry and all other tiles that fall within the cluster as subsequent entries. Occupied spaces are represented as " X ", while non-occupied spaces are represented as " - ".
vglc_random_forest.py: Attempts to predict the level of Kid Icarus that a tile is from using the numbers of different objects in the tile.
vglc_autoencoder.py: Trains an autoencoder using a set of levels to perform various tasks. Reconstruction mode encodes and decodes a single level before displaying the result. Recognition mode attempts to classify fixed-size windows of levels by the levels they came from based on the windows' encodings. Repair mode trains the autoencoder with noisy input before attempting to remove the noise from a given noisy level.

Each file has various options that can be set within the file.

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
SMBTiles		SMBTiles
trainingData		trainingData
.gitignore		.gitignore
Image to Tile.ipynb		Image to Tile.ipynb
K Means Clustering.ipynb		K Means Clustering.ipynb
LSTM_Example.ipynb		LSTM_Example.ipynb
MdMC_Tutorial.ipynb		MdMC_Tutorial.ipynb
README.md		README.md
Random Forest Level Recognition.ipynb		Random Forest Level Recognition.ipynb
VGLC Autoencoder.ipynb		VGLC Autoencoder.ipynb
k_means_0.txt		k_means_0.txt
k_means_1.txt		k_means_1.txt
k_means_10.txt		k_means_10.txt
k_means_11.txt		k_means_11.txt
k_means_12.txt		k_means_12.txt
k_means_13.txt		k_means_13.txt
k_means_14.txt		k_means_14.txt
k_means_2.txt		k_means_2.txt
k_means_3.txt		k_means_3.txt
k_means_4.txt		k_means_4.txt
k_means_5.txt		k_means_5.txt
k_means_6.txt		k_means_6.txt
k_means_7.txt		k_means_7.txt
k_means_8.txt		k_means_8.txt
k_means_9.txt		k_means_9.txt
vglc_autoencoder.py		vglc_autoencoder.py
vglc_k_means.py		vglc_k_means.py
vglc_random_forest.py		vglc_random_forest.py