The project is currently only supported on Windows 10; this may change if the game receives a native Linux port.
Install all dependencies listed above. Please refer to their respective installation guides for your platform.
Please note that you must use Pip to install SerpentAI. For all other Python packages we recommend using Conda. Also, some of the guides linked above will ask you to create a conda environment; be sure to create only one environment for all of this project's dependencies.
After setting up SerpentAI, clone the game plugin and game agent plugin to /.../SerpentAI/plugins/. This should result in the following directory tree:
├── SerpentAI
│ ├── config
│ ├── datasets
│ └── plugins
│ ├── SerpentRivalsofAetherGameAgentPlugin
│ └── SerpentRivalsofAetherGamePlugin
SerpentRivalsofAetherGameAgentPlugin contains submodules, so be sure to open it in Git Bash (or your preferred equivalent) and run git submodule update --init --recursive. In the future, you can update the submodule to the latest commit by entering it in Git Bash and running git pull remote master.
Next, you will need to open the following file in a text editor: /.../SerpentAI/plugins/SerpentRivalsofAetherGameAgentPlugin/files/helpers/roa.ini. Then, add the following lines:
[RivalsofAether]
PathToReplays = /.../users/[username]/AppData/Local/RivalsofAether/replays/
Version = x.x.x
Substitute the path given above with the path to your game's replays folder. For example, my replays folder is located at C:\Users\matth\AppData\Local\RivalsofAether\replays. You will also want to replace "x.x.x" with the installed game version, e.g. "1.0.2".
Move all of your roa files to the game's replays folder. Next, run python /plugins/SerpentRivalsofAetherGameAgentPlugin/files/helpers/manager/replaymanager.py --sort-replays to automatically move your replay files into folders corresponding with their respective game versions. This will result in a directory tree that looks something like this:
├── replays
│ ├── 00_15_07
│ ├── 00_15_08
│ ├── 00_15_09
│ ├── 00_15_10
│ ├── 00_15_11
│ ├── 01_00_02
│ ├── 01_00_03
│ ├── 01_00_05
│ ├── 01_01_02
│ ├── 01_02_01
│ └── 01_02_02
"00_15_07" refers to game version 0.15.7, "01_02_01" to 1.2.1, and so on. The frame collector agent will use the version string you entered in roa.ini to identify the correct game version folder. For example, if you are running Rivals of Aether version 1.0.2, then you should have written "1.0.2" in roa.ini. This will tell replaymanager.py to look for a folder called "01_00_02".
WARNING: Never run the collector agent without backing up your replays first. Any replays that happen to be in the replays folder (and not one of it's subfolders) will be deleted. Thus, it is essential that you run the the replay manager's sort function (as detailed above) prior to collecting.
Launch Anaconda Prompt, activate the project environment, navigate to /.../SerpentAI/, and run the following commands: 1) serpent activate SerpentRivalsofAetherGamePlugin, and 2) serpent activate SerpentRivalsofAetherGameAgentPlugin. You can also run serpent plugins to check available and activated plugins.
To collect frames effectively, we will need to override the game frame limiter setting for our game agent. Open /.../SerpentAI/config/config.plugins.yml in a text editor and update the FPS value for SerpentRivalsofAetherGameAgentPlugin. We found that 10 FPS offers a decent balance.
Make sure Steam is running and Rivals of Aether is installed. We recommend that you also turn off the Steam overlay so that inventory and friend notifications don't appear on the screen. Next, run serpent launch RivalsofAether. Once the game has finished loading the main menu, go to the replays menu by going to extras -> replays. Finally, run serpent play RivalsofAether SerpentRivalsofAetherGameAgent COLLECT in Anaconda Prompt. The game agent will begin collecting game frames and parsed player input data and dumping them as binary files located in /.../replays/frames and /.../replays/labels, respectively. A directory structure similar to this will develop:
├── replays
│ ├── 00_15_07
│ ...
│ ├── 01_02_02
│ └── frames
│ │ ├── 2017-11-07-234316128959
│ │ ├── ...
│ │ └── 2017-11-07-234241093349
│ │ ├── 0.npy
│ │ ├── ...
│ │ └── 4475.npy
│ └── labels
│ ├── 2017-11-07-234316128959
│ ├── ...
│ └── 2017-11-07-234241093349
│ ├── roa_1.npy
│ └── roa_2.npy
Avoid taking focus away from the game's window while the frame collector agent is running. If you need to stop the agent, bring Anaconda Prompt into focus. Doing so will automatically pause the agent. Next, press CTRL+C to terminate the agent. If a replay was in progress, then be sure to delete the corresponding frames and labels folders. Otherwise, these will be skipped (and thus left unfinished) when you next run the collector agent.
Please be aware that the collector agent dumps about 1 GB of frame buffer data for every 4 minutes of playback. During our initial experiments we processed just over 330 replay files, which resulted in more 40 GB of frame buffer data. If you are concerned about space requirements, you can set up a symbolic link from /.../replays/frames to a different storage device with a higher capacity.
Run python /plugins/SerpentRivalsofAetherGameAgentPlugin/files/helpers/manager/replaymanager.py --make-sets to randomly assign your frames and labels into training and testing sets. This will result in the following directory structure:
├── replays
│ ├── 00_15_07
│ ...
│ ├── 01_02_02
│ ├── frames
│ ├── labels
| └── sets
| ├── testing
│ │ ├── frames
│ │ └── labels
| └── training
│ ├── frames
│ └── labels
Due to performance considerations, data will be moved rather than copied. Therefore, your replays/frames and replays/labels folders will no longer contain any files when this operation finishes; all files will move to either replays/sets/testing or replays/sets/training.
Clone the Rivals of Aether supervised learning repository. As before, enter the repository and run git submodule update --init --recursive in order to ensure that all submodules are loaded. Next, open /.../RivalsofAetherSupervisedLearning/learning/config.ini and fill in the following fields:
[SETS]
PathToTraining = /.../training/
PathToTesting = /.../testing/
Next, run python /.../RivalsofAetherSupervisedLearning/learning/lstm.py to train and then test the model. If you wish to write your own model, consider taking advantage of the features offered by loader.py.
Your trained model will be saved to /.../RivalsofAetherSupervisedLearning/learning/rival.h5. You can copy this file into /.../SerpentAI/plugins/SerpentRivalsofAetherGameAgentPlugin/files/ml_models to use it with the provided game agent plugin.
In Anaconda Prompt navigate to /.../SerpentAI/, run serpent launch RivalsofAether, start a match, and, finally, run serpent play RivalsofAether SerpentRivalsofAetherGameAgent PLAY.