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mingsjtu authored Jan 13, 2019
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# 2048-api
A 2048 game api for training supervised learning (imitation learning) or reinforcement learning agents
A 2048 game api for training supervised learning (imitation learning)
follow ExpectiMax agent and create your own CNN model

# Code structure
* [`game2048/`](game2048/): the main package.
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* [`explore.ipynb`](explore.ipynb): introduce how to use the `Agent`, `Display` and `Game`.
* [`static/`](static/): frontend assets (based on Vue.js) for web app.
* [`webapp.py`](webapp.py): run the web app (backend) demo.
* [`evaluate.py`](evaluate.py): evaluate your self-defined agent.

* [`evaluate.py`](evaluate.py): evaluate your self-defined agent. test time = 50
* [`online_train.py`](online_train.py): get your own agent's weight.The structure of the model can be found
* [`CNN_new_141.zip`](CNN_new_141.zip): get your own agent's weight.The structure of the model can be found
# Requirements
* code only tested on linux system (ubuntu 16.04)
* Python 3 (Anaconda 3.6.3 specifically) with numpy and flask

# for train
```bash
python online_train.py
```
* you will get your own model taught by ExpectiMax agent

# To define your own agents
```python
from game2048.agents import Agent
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The code is under Apache-2.0 License.

# For EE369 students from SJTU only
Please read [here](EE369.md).
Please read [here](EE369.md).

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