-
Python 3.7.5
-
gfootball
https://github.com/google-research/football -
miniworld
https://github.com/maximecb/gym-miniworld#installation -
minigrid
https://github.com/maximecb/gym-minigrid -
Multi-Agent Particle Environment
https://github.com/openai/multiagent-particle-envs -
Overcooked-AI
https://github.com/HumanCompatibleAI/overcooked_ai -
MAgent
https://www.pettingzoo.ml/magent(Using
pip install 'pettingzoo[magent]'
if you are using zsh; Using render_from_log.py for MAgent local render) -
SMARTS
https://gitee.com/mirrors_huawei-noah/SMARTS(Put repo
SMARTS
andai_lib
under the same folder.If not using smarts, comment out
from .smarts_jidi import *
inenv/__init__.py
.If want to use NGSIM scenario, download NGSIM scenario here: https://www.dropbox.com/sh/fcky7jt49x6573z/AADUmqmIXhz_MfBcenid43hqa/ngsim?dl=0&subfolder_nav_tracking=1 and put the
ngsim
folder underSMARTS/scenarios
.If not using smarts NGSIM, comment out
from .smarts_ngsim import *
inenv/__init__.py
.) -
StartCraft II
https://github.com/deepmind/pysc2 -
Olympics Engine
https://github.com/jidiai/Competition_Olympics-Running/tree/main/olympics(Notice: Put
olympics
andai_lib
under the same folder) -
Classic
https://www.pettingzoo.ml/classicpip install pettingzoo[classic]==1.10.0
(Using
pip install 'pettingzoo[classic]==1.10.0'
if you are using zsh.) -
Torch 1.7.0
可选- 支持提交Torch训练后的模型.pth附属文件
|-- platform_lib
|-- README.md
|-- run_log.py // 本地调试运行环境
|-- examples // 提交运行文件示例 需包含 my_controller 函数输出policy
|-- random.py // 随机策略 需根据环境动作是否连续 调整 is_act_continuous 的值
|-- replay // render工具,用于非gym环境,打开replay.html上传run_log 存储的.json文件
|-- env // 游戏环境
| |-- simulators // 模拟器
| | |-- game.py
| | |-- gridgame.py // 网格类模拟器接口
| |-- obs_interfaces // observation 观测类接口
| | |-- observation.py // 目前支持Grid Vector
| |-- config.ini // 相关配置文件
| |-- chooseenv.py
| |-- snakes.py
| |-- gobang.py
| |-- reversi.py
| |-- sokoban.py
| |-- ccgame.py
- 填写算法名称或描述,选择提交环境
- 上传一个或多个文件。
- 其中必须包含一个运行文件,运行文件需包含
my_controller
函数的一个submission.py
文件。 - 附属文件支持
.pth
.py
类型文件。大小不超过100M,个数不超过5个。