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.