The source code and dockerfile for the GSW2024 AI Lab.
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from __future__ import annotations
from minigrid.core.constants import COLOR_NAMES
from minigrid.core.grid import Grid
from minigrid.core.mission import MissionSpace
from minigrid.core.world_object import (
Ball,
Box,
Key,
Slippery,
SlipperyEast,
SlipperySouth,
SlipperyNorth,
SlipperyWest,
Lava,
Goal,
Point
)
from minigrid.minigrid_env import MiniGridEnv
import numpy as np
import random
class LavaFaultyEnv(MiniGridEnv):
"""
### Registered Configurations
S: size of map SxS.
V: Version
- `MiniGrid-LavaFaultyS12-v0`
"""
def __init__(self,
size=12,
width=None,
height=None,
gap=5,
fault_probability=0.1,
per_step_penalty=0.0,
faulty_behavior=True,
obstacle_type=Lava,
randomize_start=True,
**kwargs):
self.obstacle_type = obstacle_type
self.size = size
self.gap = gap
self.fault_probability = fault_probability
self.faulty_behavior = faulty_behavior
self.previous_action = None
self.per_step_penalty = per_step_penalty
self.randomize_start = randomize_start
if width is not None and height is not None:
self.width = width
self.height = height
else:
self.width = size
self.height = size
if obstacle_type == Lava:
mission_space = MissionSpace(
mission_func=lambda: "avoid the lava and get to the green goal square"
)
else:
mission_space = MissionSpace(
mission_func=lambda: "find the opening and get to the green goal square"
)
super().__init__(
mission_space=mission_space,
width=self.width,
height=self.height,
max_steps=200,
# Set this to True for maximum speed
see_through_walls=False,
**kwargs
)
def fault(self):
return True if random.random() < self.fault_probability else False
def step(self, action: ActType) -> tuple[ObsType, SupportsFloat, bool, bool, dict[str, Any]]:
if self.step_count > 0 and self.fault():
action = self.previous_action
self.previous_action = action
obs, reward, terminated, trucated, info = super().step(action)
return obs, reward - self.per_step_penalty, terminated, trucated, info
def reset(self, **kwargs) -> tuple[ObsType, dict[str, Any]]:
self.previous_action = None
return super().reset(**kwargs)
def _gen_grid(self, width, height):
assert width >= 5 and height >= 5
# Create an empty grid
self.grid = Grid(width, height)
for row in range(1, height - 1):
if row < (height - self.gap):
self.grid.horz_wall(1, row, width - self.gap - row, Lava)
for i, col in enumerate(reversed(range(1, width - 1))):
self.grid.vert_wall(col, self.gap + i, None, Lava)
self.grid.wall_rect(0, 0, width, height)
if self.randomize_start:
self.place_agent()
else:
self.agent_pos = np.array((1, height - 2))
self.agent_dir = 3
self.mission = (
"avoid the lava and get to the green goal square"
if self.obstacle_type == Lava
else "find the opening and get to the green goal square"
)
self.put_obj(Goal(), width - 2, 1)
def disable_random_start(self):
self.randomize_start = False
def printGrid(self, init=False):
grid = super().printGrid(init)
properties_str = ""
if self.faulty_behavior:
properties_str += F"FaultProbability:{self.fault_probability}\n"
return grid + properties_str