Skip to content

MSU-AI/clash-royale-gym

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Clash Royale Env

Action Space Discrete(2304)
Observation Shape (128, 128, 3)
Observation High 255
Observation Low 0
Import import clash_royale
gymnasium.make("clash-royale", render_mode="rgb_array")

Description

Clash Royale as a Gymnasium environment. Supports Python versions 3.10 and above.

Installation

pip install git+https://github.com/MSU-AI/clash-royale-rl.git@0.0.1

Usage

  1. Import it to train your RL model
import clash_royale
env = gymnasium.make("clash-royale", render_mode="rgb_array")

The package relies on import side-effects to register the environment name so, even though the package is never explicitly used, its import is necessary to access the environment.

  1. Some sample code
# WARNING: This code is subject to change and may be OUTDATED!
import clash_royale
import gymnasium
env = gymnasium.make("clash-royale", render_mode="rgb_array")

obs, _ = env.reset()
while True:
    # Next action:
    # (feed the observation to your agent here)
    action = env.action_space.sample()

    # Processing:
    obs, reward, terminated, _, info = env.step(action)
    
    # Checking if the player is still alive
    if terminated:
        break

env.close()

Action Space

Clash Royale has the action space Discrete(2304).

Variable Meaning
x Card x-coordinate
y Card y-coordinate
z Card index in hand

Corresponding action space index of x * y * z.

Observation Space

The observation will be the RGB image that is displayed to a human player with observation space Box(low=0, high=255, shape=(128, 128, 3), dtype=np.uint8).

Version History

  • v0.0.1: initial version release with mock api calls for internal testing

About

Clash Royale Reinforcement Learning AI

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Contributors 3

  •  
  •  
  •  

Languages