Readme

I am keeping upgrading this, so the code may change everyday.

Environment

• windows 10 (We use win32 API to operate the little knight and get screenshots)
• python 3.8.8
• python liberary: find in requirments.txt
• Hollow Knight
• HP Bar mod for Hollow Knight (In order to get the boss hp to calculate the reward, please find the mod in ./hollow_knight_Data/, and then copy the mod file to the game folder)
• CUDA and cudnn for tensorflow

Usage

• Now I only write train.py but not test.py (the file is just test some base functions not for model), you can write it by yourself if you get a good model.
• I upload a saving file, if you never played this game, please move /save_file/user3.dat into save folder (usually C:\user\_username_\AppData\LocalLow\Team Cherry\Hollow Knight)
• Adjust the game resolution to 1920*1017
• Run train.py
• Keep the game window at the forefront (Since I cannot send keyboard event in the background, I tried PossMassage() in win32 API, but it did not work well. If you have any idea about sending keyboard event in the background, please let me know)
• Let the little knight stand in front of the statue of the boss in the godhome
• Press F1 to start trainning. (Also you can use F1 to stop trainning)

Code structure

• Most training configuration is in train.py

• Agent.py gets output actions from our model

• DQN.py is the learning algorithm

• Model.py defines the model we use

• ReplayMemory.py defines the experience pool for learning

• test.py is useless, I use it to test basic functions and fix bugs

• Files in ./Tool are for other functions we may use

• Actions defines actions for little knight and restart game script

• GetHp help us get our hp, boss hp, soul and location(it may have some bugs, you can fix it by yourself)

• SendKey is the API we use to send keyboard event to windows system.

• UserInput is an useless file, which I used it to train my model manually.

• WindowsAPI is used to get screenshot of the game, and key_check() is used to check which key is pressed.

• Helper defines [Reward Jugment] fucntion, and other functions we may use

Changes

• Add delay reward of an action

• Make the mdoel output an action sequence

• Use two models to output actions. One is for moving and the other is for attack/jump/skill

• Apply RESNET

• Add LSTM layers

• Merge a part of action model and move model

• Remvoe LSTM layers

• No more Q value, reward is enough, Q value is too complex to learn.

• Use kernel32 to read player Hp and hornet Hp.

• Use different criteria to evaluate move and actions.

• Do not use skill without souls

• Use more precise scoring standards