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- from gym_minigrid.minigrid import *
- from gym_minigrid.register import register
- class Room:
- def __init__(self,
- top,
- size,
- entryDoorPos,
- exitDoorPos
- ):
- self.top = top
- self.size = size
- self.entryDoorPos = entryDoorPos
- self.exitDoorPos = exitDoorPos
- class MultiRoomEnv(MiniGridEnv):
- """
- Environment with multiple rooms (subgoals)
- """
- def __init__(self,
- minNumRooms,
- maxNumRooms,
- maxRoomSize=10
- ):
- assert minNumRooms > 0
- assert maxNumRooms >= minNumRooms
- assert maxRoomSize >= 4
- self.minNumRooms = minNumRooms
- self.maxNumRooms = maxNumRooms
- self.maxRoomSize = maxRoomSize
- self.rooms = []
- super(MultiRoomEnv, self).__init__(
- gridSize=25,
- maxSteps=self.maxNumRooms * 20
- )
- def _genGrid(self, width, height):
- roomList = []
- # Choose a random number of rooms to generate
- numRooms = self._randInt(self.minNumRooms, self.maxNumRooms+1)
- while len(roomList) < numRooms:
- curRoomList = []
- entryDoorPos = (
- self._randInt(0, width - 2),
- self._randInt(0, width - 2)
- )
- # Recursively place the rooms
- self._placeRoom(
- numRooms,
- roomList=curRoomList,
- minSz=4,
- maxSz=self.maxRoomSize,
- entryDoorWall=2,
- entryDoorPos=entryDoorPos
- )
- if len(curRoomList) > len(roomList):
- roomList = curRoomList
- # Store the list of rooms in this environment
- assert len(roomList) > 0
- self.rooms = roomList
- # Randomize the starting agent position and direction
- topX, topY = roomList[0].top
- sizeX, sizeY = roomList[0].size
- self.startPos = (
- self._randInt(topX + 1, topX + sizeX - 2),
- self._randInt(topY + 1, topY + sizeY - 2)
- )
- self.startDir = self._randInt(0, 4)
- # Create the grid
- self.grid = Grid(width, height)
- wall = Wall()
- prevDoorColor = None
- # For each room
- for idx, room in enumerate(roomList):
- topX, topY = room.top
- sizeX, sizeY = room.size
- # Draw the top and bottom walls
- for i in range(0, sizeX):
- self.grid.set(topX + i, topY, wall)
- self.grid.set(topX + i, topY + sizeY - 1, wall)
- # Draw the left and right walls
- for j in range(0, sizeY):
- self.grid.set(topX, topY + j, wall)
- self.grid.set(topX + sizeX - 1, topY + j, wall)
- # If this isn't the first room, place the entry door
- if idx > 0:
- # Pick a door color different from the previous one
- doorColors = set(COLOR_NAMES)
- if prevDoorColor:
- doorColors.remove(prevDoorColor)
- # Note: the use of sorting here guarantees determinism,
- # This is needed because Python's set is not deterministic
- doorColor = self._randElem(sorted(doorColors))
- entryDoor = Door(doorColor)
- self.grid.set(*room.entryDoorPos, entryDoor)
- prevDoorColor = doorColor
- prevRoom = roomList[idx-1]
- prevRoom.exitDoorPos = room.entryDoorPos
- # Place the final goal
- while True:
- self.goalPos = (
- self._randInt(topX + 1, topX + sizeX - 1),
- self._randInt(topY + 1, topY + sizeY - 1)
- )
- # Make sure the goal doesn't overlap with the agent
- if self.goalPos != self.startPos:
- self.grid.set(*self.goalPos, Goal())
- break
- self.mission = 'traverse the rooms to get to the goal'
- def _placeRoom(
- self,
- numLeft,
- roomList,
- minSz,
- maxSz,
- entryDoorWall,
- entryDoorPos
- ):
- # Choose the room size randomly
- sizeX = self._randInt(minSz, maxSz+1)
- sizeY = self._randInt(minSz, maxSz+1)
- # The first room will be at the door position
- if len(roomList) == 0:
- topX, topY = entryDoorPos
- # Entry on the right
- elif entryDoorWall == 0:
- topX = entryDoorPos[0] - sizeX + 1
- y = entryDoorPos[1]
- topY = self._randInt(y - sizeY + 2, y)
- # Entry wall on the south
- elif entryDoorWall == 1:
- x = entryDoorPos[0]
- topX = self._randInt(x - sizeX + 2, x)
- topY = entryDoorPos[1] - sizeY + 1
- # Entry wall on the left
- elif entryDoorWall == 2:
- topX = entryDoorPos[0]
- y = entryDoorPos[1]
- topY = self._randInt(y - sizeY + 2, y)
- # Entry wall on the top
- elif entryDoorWall == 3:
- x = entryDoorPos[0]
- topX = self._randInt(x - sizeX + 2, x)
- topY = entryDoorPos[1]
- else:
- assert False, entryDoorWall
- # If the room is out of the grid, can't place a room here
- if topX < 0 or topY < 0:
- return False
- if topX + sizeX > self.gridSize or topY + sizeY >= self.gridSize:
- return False
- # If the room intersects with previous rooms, can't place it here
- for room in roomList[:-1]:
- nonOverlap = \
- topX + sizeX < room.top[0] or \
- room.top[0] + room.size[0] <= topX or \
- topY + sizeY < room.top[1] or \
- room.top[1] + room.size[1] <= topY
- if not nonOverlap:
- return False
- # Add this room to the list
- roomList.append(Room(
- (topX, topY),
- (sizeX, sizeY),
- entryDoorPos,
- None
- ))
- # If this was the last room, stop
- if numLeft == 1:
- return True
- # Try placing the next room
- for i in range(0, 8):
- # Pick which wall to place the out door on
- wallSet = set((0, 1, 2, 3))
- wallSet.remove(entryDoorWall)
- exitDoorWall = self._randElem(sorted(wallSet))
- nextEntryWall = (exitDoorWall + 2) % 4
- # Pick the exit door position
- # Exit on right wall
- if exitDoorWall == 0:
- exitDoorPos = (
- topX + sizeX - 1,
- topY + self._randInt(1, sizeY - 1)
- )
- # Exit on south wall
- elif exitDoorWall == 1:
- exitDoorPos = (
- topX + self._randInt(1, sizeX - 1),
- topY + sizeY - 1
- )
- # Exit on left wall
- elif exitDoorWall == 2:
- exitDoorPos = (
- topX,
- topY + self._randInt(1, sizeY - 1)
- )
- # Exit on north wall
- elif exitDoorWall == 3:
- exitDoorPos = (
- topX + self._randInt(1, sizeX - 1),
- topY
- )
- else:
- assert False
- # Recursively create the other rooms
- success = self._placeRoom(
- numLeft - 1,
- roomList=roomList,
- minSz=minSz,
- maxSz=maxSz,
- entryDoorWall=nextEntryWall,
- entryDoorPos=exitDoorPos
- )
- if success:
- break
- return True
- class MultiRoomEnvN2S4(MultiRoomEnv):
- def __init__(self):
- super().__init__(
- minNumRooms=2,
- maxNumRooms=2,
- maxRoomSize=4
- )
- class MultiRoomEnvN6(MultiRoomEnv):
- def __init__(self):
- super().__init__(
- minNumRooms=6,
- maxNumRooms=6
- )
- register(
- id='MiniGrid-MultiRoom-N2-S4-v0',
- entry_point='gym_minigrid.envs:MultiRoomEnvN2S4',
- reward_threshold=1000.0
- )
- register(
- id='MiniGrid-MultiRoom-N6-v0',
- entry_point='gym_minigrid.envs:MultiRoomEnvN6',
- reward_threshold=1000.0
- )
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