CS 175 · UC Irvine · AI Project

The Game of 2048,
Taught to Think

A deep reinforcement learning experiment pitting three algorithms against each other — DQN vs MCTS vs PPO — to see which one masters the art of exponential tile merging.

PPO agent reaching 2048 tile in 2048

PPO reaches
tile 2048

The Proximal Policy Optimization agent navigates the 4×4 grid through trial and error, learning corner strategies and merge sequences that push tiles to their theoretical maximum.

2048 Best Tile
MCTS
& PPO
Algorithm
3 Models

Project Reports

03 documents

References

05 sources
PowerOf2 Source code on GitHub
View Repository ↗