Knights Archers Zombies PPO

CS 4180 Reinforcement Learning Final Project - Implementing PPO in a multi-agent environment

Read the paper here.

Environment configuration

knights_archers_zombies_v10.parallel_env(
    render_mode="human",
    spawn_rate=15,
    vector_state=False,
    num_archers=2,
    num_knights=2,
    max_zombies=30,
)

Running the code

NOTE: PettingZoo does not work on Windows, so Linux is recommended.

First, create a virtualenv and install the required libraries/packages.

python3 -m venv .venv # this creates a virtual environment called .venv
source .venv/bin/activate
pip3 install -r requirements.txt

To run the code,

python3 mappo.py

References

1. Schulman, J., Wolski, F., Dhariwal, P., Radford, A., & Klimov, O. (2017). Proximal Policy Optimization Algorithms. CoRR, abs/1707.06347. Retrieved from arXiv.

2. Yu, C., Velu, A., Vinitsky, E., Wang, Y., Bayen, A. M., & Wu, Y. (2021). The Surprising Effectiveness of MAPPO in Cooperative, Multi-Agent Games. CoRR, abs/2103.01955. Retrieved from arXiv.

3. Terry, J. K., Black, B., & Hari, A. (2020). SuperSuit: Simple Microwrappers for Reinforcement Learning Environments. arXiv preprint arXiv:2008.08932. Retrieved from arXiv.