Bomberman Learning Environment
This project uses ML-Agent plugin for Unity3D version 0.5, so the prerequisites are:
Unity3d Game engine > 5.0.0 (https://unity3d.com/pt/get-unity/download)
ML-Agents 0.5v Plugin (https://github.com/icaro56/ml-agents (fork with some changes))
It's important install the ML-Agents dependencies.
we need change the .NetFramework to 4.6 and mark the Run Background checkbox case this is not configured.
Edit->Project Settings->Players
Resolution and Presentation
Run in Background
Other Settings
Configuration
Script Runtime Version
set 4.6
We created a tag named bomberman_experiment both in this repository and in our ml-agent fork respository to expose which Bomberman Learning Environment version was used to run the experiments that were done in the paper. This tag is to PPO and LSTM trainings. The Imitation Learning uses the most up-to-date version.
All statistics and all templates generated in agent training in this environment can be found in Google Drive: https://drive.google.com/file/d/15ZEPz4j3FvPfEAhPd-ZrUN5Hj5EE9ajQ/view?usp=sharing
PPO Agents with Binary Flag State Representation: https://youtu.be/qM8n9tmvBdw
PPO Agents with Normalized Binary Flag State Representation: https://youtu.be/_YlMBlMhHL8
PPO Agents with ICAART State Representation: https://youtu.be/eIjo7Vat-aE
PPO Agents with ZerOrOne State Representation: https://youtu.be/SC2vUTtlmSA
PPO Agents with Hybrid State Representation: https://youtu.be/w7noFJ_w2GQ
PPO Agents Tournament Example Hybrid x ZeroOrOne x ICAART x Normalized Binary Flag: https://youtu.be/oRKZfGiBlqs
PPO+LSTM Agents with Hybrid State Representation: https://youtu.be/sJ79-OHrFGM
PPO versus PPO+LSTM: https://youtu.be/QQ4kThziFa8
BC+PPO versus PPO+LSTM: https://youtu.be/2ccxyoHbI4o