FJJLeon / 2048-api

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

2048-api

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

For TA

• if you want to evaluate the model, run blow command in the path of /2048-api

    python evaluate.py

note: the models should be in the path of /2048-api/model

• if you want to test train the model

1. first modify the import part of myAgent2.py as below

    # test use
    #from game2048.agents import Agent, ExpectiMaxAgent
    #from game2048.game import Game
    # train use
    from agents import Agent, ExpectiMaxAgent
    from game import Game

note: if there exists models in the path /2048-api/model, set firstTime to False in instantiation myOwnAgent in the last part of myAgent2.py, or set to True

    myAgent = myOwnAgent(
        game=tmpGame,
        maxPower=16, 
        modelLevel=[256, 512, 900],
        firstTime=False)

2. then run blow command in the path of /2048-api

    python game2048/myAgent2.py

Code structure

• game2048/: the main package.
  • game.py: the core 2048 Game class.
  • agents.py: the Agent class with instances.
  • displays.py: the Display class with instances, to show the Game state.
  • expectimax/: a powerful ExpectiMax agent by here.
  • myAgent2.py: my weak agent.
• explore.ipynb: introduce how to use the Agent, Display and Game.
• static/: frontend assets (based on Vue.js) for web app.
• webapp.py: run the web app (backend) demo.
• evaluate.py: evaluate your self-defined agent.

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

LICENSE

The code is under Apache-2.0 License.

For EE369 students from SJTU only

Please read here.