Some ugly codes of TD-Learning and Expectimax Search for game 2048.
(Developed by K.H Yeh and I.C Wu from CGI-Lab @NCTU).
We use TD-Lambda and several features to train 2048 by self-playing.
Those features includes:
Number of large tiles
Number of pairs of merge-able tiles
Number of disintinct tiles
Number of empty tiles
Number of layered tiles (Twice larger or smaller than neighbors)
The download link for the trained features weights for this program:
Performances: (1000 games)
The AI is on the website: http://2048.aigames.nctu.edu.tw/
To see the record of reaching 65536: http://2048.aigames.nctu.edu.tw/replay.php
|Search depth||2.5 (5)|
The program's result along with other experiments are in the IEEE Journal Paper: http://ieeexplore.ieee.org/document/7518633/