Skip to content
/ 2048-NN Public
forked from ovolve/2048-AI

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

License

Notifications You must be signed in to change notification settings

tjwei/2048-NN

Repository files navigation

2048 Deep Learning AI

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 >92% of the games. It reaches 4096 in >72% of the games and reaches 8192 in >23% of the games.

It may sometimes fails 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 0.018% 0.018% 100.000%
8192 23.583% 23.601% 99.982%
4096 49.354% 72.955% 76.399%
2048 19.421% 92.376% 27.045%
1024 5.591% 97.967% 7.624%
512 1.483% 99.450% 2.033%
256 0.342% 99.792% 0.550%
128 0.138% 99.930% 0.208%
64 0.049% 99.979% 0.070%
32 0.016% 99.995% 0.021%
16 0.003% 99.998% 0.005%
8 0.002% 100.000% 0.002%

or in graph

The average score is 73535.7 and the average length of a game is 3279.8 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 30. You can make it run much faster with a smaller delay.

About

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

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 56.0%
  • CSS 19.5%
  • JavaScript 18.0%
  • Python 3.7%
  • HTML 2.8%