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Educational API for developing ML (imitation learning or reinforcement learning) agents to play game 2048

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2048-api

A 2048 game api for training supervised learning (imitation learning) or reinforcement learning agents

Code structure

Requirements

  • code only tested on linux system (ubuntu 16.04)
  • Python 3 (Anaconda 3.6.3 specifically) with numpy and flask

To define your own agents

from game2048.agents import Agent

class YourOwnAgent(Agent):

    def step(self):
        '''To define the agent's 1-step behavior given the `game`.
        You can find more instance in [`agents.py`](game2048/agents.py).
        
        :return direction: 0: left, 1: down, 2: right, 3: up
        '''
        direction = some_function(self.game)
        return direction

To compile the pre-defined ExpectiMax agent

cd game2048/expectimax
bash configure
make

To run the web app

python webapp.py

demo

LICENSE

The code is under Apache-2.0 License.

For EE369 / EE228 students from SJTU

Please read course project requirements and description.

Acknowledgement

The wrapped ExpectiMax agent is based on nneonneo/2048-ai.

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