AI Mahjong
This project is both a "game" and a way to show the power of my discard prediction AI
Average prediction rate 57%
This project is both a "game" and a way to show the power of my discard prediction AI
Average prediction rate 57%
Top1 prediction : 80.7%
Top3 prediction : 95.1%
Top5 prediction : 97%
Confidence(average of strongest prediction) : 73%
Extracted from Tenhou.net, the largest online Mahjong platform in Japan.
Kaggle dataset: https://www.kaggle.com/datasets/trongdt/japanese-mahjong-board-states/data
Data are mapped on a 511 array, following this example picture.
To do List:
- Better Hand call system
- Riichi management
Some data are non retrievable like red dora.
Those data are Pov based,
The player positions are:
p0: The POV player
p1: The player seated right for the POV player, i.e. Kamicha
p2: The player seated directly across the POV player, i.e. Toimen
p3: The player seated left for the POV player, i.e. Shimocha
Since it's Pov based retrieving the discard order for the "game" part of this project was a bit challenging.
The first 34 elements of the array comprise the Metadata of the Mahjong state.
The model was trained on 1000 games from Tenhou 7dan+ players.
