duducheng / 2048 Api
Licence: apache-2.0
Educational API for developing ML (imitation learning or reinforcement learning) agents to play game 2048
Stars: ✭ 111
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2048-api
A 2048 game api for training supervised learning (imitation learning) or reinforcement learning agents
Code structure
-
game2048/
: the main package.-
game.py
: the core 2048Game
class. -
agents.py
: theAgent
class with instances. -
displays.py
: theDisplay
class with instances, to show theGame
state. -
expectimax/
: a powerful ExpectiMax agent by here.
-
-
explore.ipynb
: introduce how to use theAgent
,Display
andGame
. -
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 / EE228 students from SJTU
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