WhatIThinkAbout

from .baby_robot_env_v0 import BabyRobotEnv_v0
from .baby_robot_env_v1 import BabyRobotEnv_v1

WhatIThinkAbout

# animate an image on the canvas
baby_robot = Image.from_file('images/baby_robot.png')
robot_size = 64
canvas[1].clear()
y = 70
for x in range(0,200,4):   
  with hold_canvas(canvas[1]):
    canvas[1].clear_rect(x, y, robot_size)                        
    canvas[1].draw_image(baby_robot, x, y )       
  sleep(0.1)

WhatIThinkAbout

from ipycanvas import Canvas

cell_pixels = 64           # pixel dimensions of a grid square   
grid_width  = 3            # number of horizontal cells
grid_height = 3            # number of vertical cells 

width_pixels  = grid_width  * cell_pixels  # total horizontal pixels
height_pixels = grid_height * cell_pixels  # total vertical pixels

canvas = Canvas(width=width_pixels, height=height_pixels)

WhatIThinkAbout

class BabyRobotEnv_v2( BabyRobotEnv_v1 ):

  metadata = {'render_modes': ['human']}

  def __init__(self, **kwargs):
      super().__init__(**kwargs)

      # the start and end positions in the grid
      # - by default these are the top-left and bottom-right respectively
      self.start = kwargs.get('start',[0,0])

WhatIThinkAbout

from enum import IntEnum

''' simple helper class to enumerate actions in the grid levels '''
class Actions(IntEnum):  
    Stay  = 0    
    North = 1
    East  = 2
    South = 3
    West  = 4

WhatIThinkAbout

from gymnasium.envs.registration import register

register(
    id='BabyRobotEnv-v0',
    entry_point='babyrobot.envs:BabyRobotEnv_v0',
)

register(
    id='BabyRobotEnv-v1',
    entry_point='babyrobot.envs:BabyRobotEnv_v1',

WhatIThinkAbout

from setuptools import setup

setup(
    name="babyrobot",
    version="1.0.0",    
    install_requires=['gymnasium']    
)

WhatIThinkAbout

from stable_baselines3.common.env_checker import check_env

# create an instance of our custom environment
env = BabyRobotEnv_v1()

# returns nothing if the environment is verified as ok
check_env(env)

WhatIThinkAbout

import numpy as np
from gymnasium.spaces import Discrete,MultiDiscrete


class BabyRobotEnv_v1(gym.Env):

    def __init__(self, **kwargs):
        super().__init__()

        # dimensions of the grid

WhatIThinkAbout

class BabyRobotEnv_v0(gym.Env):
    
    def __init__(self):
        super().__init__()
        pass

    def step(self, action):        
        state = 1    
        reward = -1            
        terminated = True