roth1002 / 2048-nn

A Deep Learning AI for 2048 (2048:94.15%, 4096:78.48%, 8192: 34.5% 16384: 0.177%)

A 2048 Deep Learning AI (that does not suck)

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.