Grzego / game-level-gan

Generating balanced multiplayer game levels with GANs and RL.

Generating balanced multiplayer game levels with GANs and RL

The main idea of this project was to automatically, with as little input as possible, generate game levels. As a level generation is a rather broad area we focused on a more clearly defined goal. And we decided to train a generator capable of generating boards that are fair for all the players involved in the game.

As a proof of concept, a simple racing game was chosen to be used to evaluate if algorithms work. More details are available in my thesis.

Concept

Evaluation & Results

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How to run

To run experiments for yourself, you can execute the following commands.

Train agents

python train-agents.py

This command will run training on a few random predefined tracks. When agents are sufficiently trained, which will probably take quite a lot of time, you can stop the script.

Train generator and discriminator

python train-gan.py --agents=<path_to_dir_with_trained_agents>

Play with generator

With the trained generator you can evaluate whether the tracks it generates are fairer:

python evaluate.py --generator=<path_to_dir_with_generator> \
                   --agents=<path_to_dir_with_trained_agents>

You can also explore how the latent space looks like using the following command (this script requires the pyforms==3.0.0 to be installed):

python explore.py --generator=<path_to_dir_with_generator>

Or run latent interpolation:

python latent-interpolation.py --generator=<path_to_dir_with_generator>