Gobigger-Explore

🔮 GoBigger Challenge 2021 Baseline

en/中文

🤖 Introduction

This is the baseline of GoBigger Multi-Agent Decision Intelligence Challenge in 2021. The baseline is based on OpenDILab and aims to provide a simple entry-level method. Participants can build agents by extending the baseline method provided. In addition, Opendilab's modular structure allows participants to easily get started, and it provides a wealth of reinforcement learning algorithms for participants to use. This baseline is a good starting point, especially for entry-level researchers who are familiar with multi-agent decision AI problems.

🚀 Release Version

The current version is the latest version v-0.2.0.

1. What needs to be optimized in the future
   • Variable length features lead to potential GPU memory explosion risk.
   • Better reward function design.
2. Version-0.2.0
   • Fix the ckpt bug to improve the accuracy of the evaluator.
   • Fix replay_buffer bug
   • Brand new feature engineering to improve convergence speed.
   • Replay_buffer stores variable-length features to improve data utilization and training speed.
3. Version-0.1.0
   • Primary version link

👇 Getting Started

1. System environment

   • Core 16
   • GPU A100(40G)
   • Memory 50G

2. Baseline Config

   • The default config is the config used in this experiment. Participants can modify it according to the system environment.
   • The size of replay_buffer_size needs to be set according to the size of RAM.
   • The size of batch_size needs to be set according to the size of the GPU memory.

3. Install the necessary packege

    # Install DI-engine
    git clone https://github.com/opendilab/DI-engine.git
    cd YOUR_PATH/DI-engine/
    pip install -e . --user

    # Install Env Gobigger
    git clone https://github.com/opendilab/GoBigger.git
    cd YOUR_PATH/GoBigger/
    pip install -e . --user

4. Start training

    # Download baseline
    git clone https://github.com/opendilab/Gobigger-Explore.git
    cd my_submission/entry/
    python gobigger_vsbot_baseline_main.py

5. Evaluator and Save game videos

    cd my_submission/entry/
    python gobigger_vsbot_baseline_eval.py --ckpt YOUR_CKPT_PATH

🎯 Result

We released training log information, checkpoints, and evaluation videos. Below is the download link,

• Baidu Netdisk Link
  • Extraction code: u4i6
• Google Drive Link

😍 Resources

• Challenge Page Link
• Challenge Repo Github Link
• DI-engine Repo Github Link
• GoBigger Repo Github Link