The game that both plays and develops itself
More elaborated, this project is about pitting AI agents against a procedural level generator. The level generator will adapt to the player over time. For illustration purposes, we have designed some rule-based agents who use very specific strategies, to see how the generator "responds" to that. For the full experiment, we want to run a learning agent (using a DQN), that will learn to exploit the environment, all while the environment learns to exploit the agent.
- Jonathan Jørgensen
- Pedro M. Fernandes
- Even Klemsdal
- Niels NTG Poldervaart
- Run the run_all.sh script. This will evolve a population of difficult maps for each one of the Rule Based Agents.
- Run the run_dqn.py file with the --train argument and the name of the training session. Example: "python3 run_dqn.py --train Q01"
pygame
numpy
gym
pillow
scipy
stable_baselines3
