I didn't think neural network is particularly suitable for solving 2048 puzzle, but I implement one anyway. Turns out the result is not too bad, at least much better than I expected.
See it in action http://tjwei.github.io/2048-NN/ and in Video https://www.youtube.com/watch?v=oRC2W38lxIE
Nueral Netowrk AI for the game 2048.
It is a fork of http://ov3y.github.io/2048-AI/ and replace the AI part by a neural network.
The neural network is pretrained using Theano and lasgane by observing simulated games and supervised by an advance AI https://github.com/nneonneo/2048-ai
The trained neural network can achieve 2048+ in >94% of the games. It reaches 4096 in >78% of the games and reaches 8192 in >34% of the games There is a small chance(0.1%~0.2%) the AI can reach a max tile of 16384.
It may sometimes ended with an embarrassingly low score.
The following is the result of 100K games played by the neural network
| max tile | % of games | accumulated % | reversed accumulated % |
|---|---|---|---|
| 16384 | 0.177% | 0.177% | 100.000% |
| 8192 | 34.500% | 34.677% | 99.823% |
| 4096 | 43.819% | 78.496% | 65.323% |
| 2048 | 15.656% | 94.152% | 21.504% |
| 1024 | 4.340% | 98.492% | 5.848% |
| 512 | 1.144% | 99.636% | 1.508% |
| 256 | 0.261% | 99.897% | 0.364% |
| 128 | 0.064% | 99.961% | 0.103% |
| 64 | 0.026% | 99.987% | 0.039% |
| 32 | 0.007% | 99.994% | 0.013% |
| 16 | 0.005% | 99.999% | 0.006% |
| 8 | 0.001% | 100.000% | 0.001% |
or in graph
The average score is 85351.8 and the average length of a game is 3733.6 steps.
The following graph shows how many games left after certain steps in the 100K simulations:
The graph indicates that the AI performs relatively weak in early stage of the game.
Without the help of human made features and heuristics like what is used in https://github.com/nneonneo/2048-ai , the network can still reaches at least 75% success rate for the same network architecture.
A much smaller model trained without using any human made features and heuristics reaches 47% of success rate, can be found at http://github.ocm/tjwei/rl/
The animationDelay is set to 10. You can make it run faster or slower with a different delay time.