Minecart-Deterministic¶
Action Space |
Discrete(6) |
Observation Shape |
(7,) |
Observation High |
[1. 1. 1. 1. 1. 1. 1.] |
Observation Low |
[-1. -1. -1. -1. -1. -1. -1.] |
Reward Shape |
(3,) |
Reward High |
[1.5 1.5 0. ] |
Reward Low |
[ 0. 0. -1.] |
Import |
|
Description¶
Agent must collect two types of ores and minimize fuel consumption. From Abels et al. 2019.
Observation Space¶
The observation is a 7-dimensional vector containing the following information:
2D position of the cart
Speed of the cart
sin and cos of the cart’s orientation
porcentage of the capacity of the cart filled If image_observation is True, the observation is a 3D image of the environment.
Action Space¶
The action space is a discrete space with 6 actions:
0: Mine
1: Left
2: Right
3: Accelerate
4: Brake
5: None
Reward Space¶
The reward is a 3D vector:
0: Quantity of the first minerium that was retrieved to the base (sparse)
1: Quantity of the second minerium that was retrieved to the base (sparse)
2: Fuel consumed (dense)
Starting State¶
The cart starts at the base on the upper left corner of the map.
Episode Termination¶
The episode ends when the cart returns to the base.
Arguments¶
render_mode: The render mode to use. Can be “rgb_array” or “human”.
image_observation: If True, the observation is a RGB image of the environment.
frame_skip: How many times each action is repeated. Default: 4
incremental_frame_skip: Whether actions are repeated incrementally. Default: True
config: Path to the .json configuration file. See the default configuration file for more information: https://github.com/Farama-Foundation/MO-Gymnasium/blob/main/mo_gymnasium/envs/minecart/mine_config.json
Credits¶
The code was refactored from Axel Abels’ source.