class Game(Simulator):
def __init__(self, xsize, ysize, occlusions=[]):
self.AgentHome = COORD(int(floor((xsize-1)/2)), 0)
self.PredatorNum = 1
self.PredatorHome = COORD(0, 0)
self.ChaseProbability = 0.75
self.MoveProbability = 0.5
self.Discount = 0.95
self.GoalPos = COORD(int(floor((xsize-1)/2)), ysize-1)
self.Grid = Grid(xsize, ysize)
self.NumActions = 4
self.NumObservations = 2
Simulator.__init__(self, self.NumActions, self.NumObservations, self.Discount)
self.Occlusions = occlusions
self.RewardClearLevel = 1000
self.RewardDefault = -1
self.RewardDie = -100
self.RewardHitWall = -25
self.RewardRange = 100
self.State = GameState()
self.State.AgentPos = self.AgentHome
self.State.PredatorPos = self.PredatorHome
def GetPossiblePredatorLocations(self):
allPredatorLocations = [COORD(x, y) for x in range(self.XSize) for y in range(self.YSize)]
invalidPredatorLocations = [self.GoalPos, self.AgentHome] + self.Occlusions
return list(set(allPredatorLocations) - set(invalidPredatorLocations))
def GetValidPredatorLocations(self):
allPredatorLocations = [COORD(x, y) for x in range(self.XSize) for y in range(self.YSize)]
invalidPredatorLocations = [self.GoalPos, self.AgentHome] + self.Occlusions
for predator in allPredatorLocations:
if self.Grid.VisualRay((self.AgentHome).Copy(), predator.Copy(), self.Occlusions)[0]:
invalidPredatorLocations.append(predator)
self.StartPredatorLocations = list(set(allPredatorLocations) - set(invalidPredatorLocations))
def Copy(self, state):
newState = GameState()
newState.AgentPos = state.AgentPos
newState.AgentDir = state.AgentDir
newState.PredatorPos = state.PredatorPos
newState.PredatorDir = state.PredatorDir
newState.PredatorSpeedMult = state.PredatorSpeedMult
newState.PredatorBeliefState = state.PredatorBeliefState
return newState
def Validate(self, state):
assert(self.Grid.Inside(state.AgentPos))
assert(self.Grid.Inside(state.PredatorPos))
def Valid(self, pos):
if self.Grid.Inside(pos) and pos not in self.Occlusions:
return True
return False
def NextPos(self, fromCoord, dir):
nextPos = fromCoord + Compass[dir]
if self.Valid(nextPos):
return nextPos
else:
return Compass[COMPASS.NAA]
def Step(self, state, action):
reward = self.RewardDefault
state.AgentDir = action
newpos = self.NextPos(state.AgentPos, action)
if self.Valid(newpos):
state.AgentPos = newpos
else:
reward += self.RewardHitWall
observation = 0
hitPredator = 0
if state.AgentPos == state.PredatorPos:
reward += self.RewardDie
return True, state, observation, reward # Terminate death
if self.PredatorObservation(state):
state.PredatorBeliefState = [state.AgentPos]
else:
state.PredatorBeliefState = self.PredatorAgentPosPropogation(state)
previousPredatorLocation = state.PredatorPos
state, hitPredator = self.MovePredator(state, Bernoulli(self.MoveProbability), previousPredatorLocation)
observation = self.MakeObservation(state, action)
if hitPredator:
reward += self.RewardDie
return True, state, observation, reward #Terminate death
if state.AgentPos == self.GoalPos:
reward += self.RewardClearLevel
return True, state, observation, reward #Terminate goal state
state.Depth += 1
return False, state, observation, reward
def MakeObservation(self, state, action):
observation = 0
# Predator Observation
if self.Grid.VisualRay((state.AgentPos).Copy(), (state.PredatorPos).Copy(), self.Occlusions)[0]:
observation = 1
return observation
def PredatorObservation(self, state):
predatorObservation, _ = self.Grid.VisualRay((state.AgentPos).Copy(), (state.PredatorPos).Copy(),
self.Occlusions)
return predatorObservation
def PredatorAgentPosPropogation(self, state):
copyState = self.Copy(state)
N2 = 15
N1 = 15
allPossibleAgentNewPositions = [copyState.PredatorBeliefState[0]]
testedAgentPositions = []
for n1 in range(N1):
try:
agentPosition = copyState.PredatorBeliefState[Random(0, len(copyState.PredatorBeliefState))]
except IndexError:
break
propogateState = self.Copy(copyState)
propogateState.AgentPos = agentPosition
if self.PredatorObservation(propogateState):
continue
newAgentPositions = []
for n2 in range(N2):
for action in range(self.NumActions):
newAgentPosition = self.NextPos(propogateState.AgentPos, action)
if self.Valid(newAgentPosition) and newAgentPosition != copyState.PredatorPos:
newAgentPositions.append(newAgentPosition)
if newAgentPositions:
allPossibleAgentNewPositions.extend(newAgentPositions)
for agentCoord in copyState.PredatorBeliefState:
if agentCoord not in testedAgentPositions:
allPossibleAgentNewPositions.append(agentCoord)
return allPossibleAgentNewPositions
def MovePredator(self, state, move, previousPredatorLocation):
numberOfMoves = 1
observation = self.PredatorObservation(self.Copy(state))
try:
believedAgentPosition = state.PredatorBeliefState[0]
except IndexError:
if observation:
believedAgentPosition = (state.AgentPos).Copy()
state.PredatorBeliefState = [(state.AgentPos).Copy()]
else:
allAgentLocations = [COORD(x, y) for x in range(self.XSize) for y in range(self.YSize)]
invisibleAgentLocations = [coord for coord in allAgentLocations if
self.Grid.VisualRay(coord, (state.PredatorPos).Copy(), self.Occlusions)]
validAgentLocations = list(set(invisibleAgentLocations) - set(self.Occlusions))
state.PredatorBeliefState = validAgentLocations
if len(state.PredatorBeliefState) > 1:
believedAgentPosition = state.PredatorBeliefState[Random(0, len(state.PredatorBeliefState))]
numberOfMoves = 1
if move:
numberOfMoves = state.PredatorSpeedMult
believedState = self.Copy(state)
believedState.AgentPos = believedAgentPosition
believedState.AgentPos = (state.AgentPos).Copy()
for i in range(numberOfMoves):
if Bernoulli(self.ChaseProbability) or (i > 0 and len(self.Occlusions) > 15):
believedState = self.MovePredatorAggressive(believedState, previousPredatorLocation)
else:
believedState = self.MovePredatorRandom(believedState)
state.PredatorPos = believedState.PredatorPos
if state.AgentPos == state.PredatorPos:
return state, (state.AgentPos == state.PredatorPos)
return state, (state.AgentPos == state.PredatorPos)
def MovePredatorRandom(self, state):
copyState = self.Copy(state)
predatorPos = copyState.PredatorPos
testedActions = []
while True:
action = Random(0, 4)
testedActions.append(action)
newpos = self.NextPos(predatorPos, action)
if self.Valid(newpos):
break
if set(testedActions) == {0, 1, 2, 3}:
newpos = copyState.PredatorPos
break
copyState.PredatorPos = newpos
copyState.PredatorDir = action
return copyState
def MovePredatorAggressive(self, state, previousPredatorLocation):
newState = self.Copy(state)
bestDist = self.Grid.GetXSize() + self.Grid.GetYSize()
bestPos = state.PredatorPos
bestDir = -1
agentPos = state.AgentPos
predatorPos = state.PredatorPos
for dir in range(0, 4):
dist = AggressiveDirectionalDistance(agentPos, predatorPos, dir)
newpos = self.NextPos(predatorPos, dir)
if dist <= bestDist and self.Valid(newpos) and newpos != previousPredatorLocation:
bestDist = dist
bestPos = newpos
bestDir = dir
newState.PredatorPos = bestPos
newState.PredatorDir = bestDir
return newState
class Game(Simulator):
def __init__(self,
xsize,
ysize,
occlusions=[],
visualrange=None,
verbose=False):
self.AgentHome = COORD(int(floor((xsize - 1) / 2)), 0)
self.PredatorNum = 1
self.PredatorHome = COORD(0, 0)
self.ChaseProbability = 0.75
self.MoveProbability = 0.5
self.Discount = 0.95
self.GoalPos = COORD(int(floor((xsize - 1) / 2)),
ysize - 1) #int(floor((xsize-1)/2))
self.Grid = Grid(xsize, ysize)
self.NumActions = 4
self.VisualRange = visualrange
self.Occlusions = occlusions
if not visualrange:
self.NumObservations = 2
else:
self.VisionObservationBit = len(
self.Grid.VisualArea(COORD(0, 0), 0, self.VisualRange))
self.NumObservations = self.VisionObservationBit #1 << (self.VisionObservationBit)
visualArea = self.Grid.VisualArea(self.AgentHome, 0,
self.VisualRange)
Simulator.__init__(self, self.NumActions, self.NumObservations,
self.GoalPos, occlusions, self.Discount)
self.RewardClearLevel = 1000
self.RewardDefault = -1
self.RewardDie = -100
self.RewardHitWall = -25
self.RewardRange = 100
self.State = GameState()
self.State.AgentPos = self.AgentHome
self.State.PredatorPos = self.PredatorHome
self.XSize = xsize
self.YSize = ysize
if verbose:
#self.Display = Display(xsize, ysize, 'game')
self.InitializeDisplay()
def GetValidPredatorLocations(self):
allPredatorLocations = [
COORD(x, y) for x in range(self.XSize) for y in range(self.YSize)
]
invalidPredatorLocations = [self.GoalPos, self.AgentHome
] + self.Occlusions
for predator in allPredatorLocations:
if self.Grid.VisualRay((self.AgentHome).Copy(), predator.Copy(),
self.Occlusions)[0]:
invalidPredatorLocations.append(predator)
self.StartPredatorLocations = list(
set(allPredatorLocations) - set(invalidPredatorLocations))
def FreeState(self, state):
del state
def InitializeDisplay(self):
state = self.CreateStartState()
self.DisplayState(state)
def Copy(self, state):
newState = GameState()
newState.AgentPos = state.AgentPos
newState.AgentDir = state.AgentDir
newState.PredatorPos = state.PredatorPos
newState.PredatorDir = state.PredatorDir
newState.PredatorSpeedMult = state.PredatorSpeedMult
newState.Depth = state.Depth
newState.PredatorBeliefState = state.PredatorBeliefState
return newState
def Validate(self, state):
assert (self.Grid.Inside(state.AgentPos))
assert (self.Grid.Inside(state.PredatorPos))
def CreateStartState(self):
state = GameState()
state = self.NewLevel(state)
predLocation = (state.PredatorPos).Copy()
if self.PredatorObservation(state):
state.PredatorBeliefState = [state.AgentPos]
else:
allAgentLocations = [
COORD(x, y) for x in range(self.XSize)
for y in range(self.YSize)
]
validAgentLocations = list(
set(allAgentLocations) - set(self.Occlusions))
invisibleAgentLocations = [
coord for coord in validAgentLocations
if self.Grid.VisualRay(coord, predLocation, self.Occlusions)
]
state.PredatorBeliefState = invisibleAgentLocations
return state
def CreateRandomStartState(self):
state = GameState()
state = self.NewLevel(state)
self.GetValidPredatorLocations()
predLocation = (state.PredatorPos).Copy()
if self.PredatorObservation(state):
state.PredatorBeliefState = [state.AgentPos]
else:
allAgentLocations = [
COORD(x, y) for x in range(self.XSize)
for y in range(self.YSize)
]
validAgentLocations = list(
set(allAgentLocations) - set(self.Occlusions))
invisibleAgentLocations = [
coord for coord in validAgentLocations
if self.Grid.VisualRay(coord, predLocation, self.Occlusions)
]
state.PredatorBeliefState = invisibleAgentLocations
agentObservation = np.zeros(self.NumActions)
for scan in range(self.NumActions):
agentObservation[scan] = self.MakeObservation(state, scan)
if agentObservation.any():
return state
state.PredatorPos = self.StartPredatorLocations[Random(
0, len(self.StartPredatorLocations))]
return state
def NewLevel(self, state):
state.AgentPos = self.AgentHome
state.AgentDir = -1
state.PredatorPos = self.PredatorHome
state.PredatorDir = -1
state.PredatorSpeedMult = 2
state.Depth = 0
state.PredatorBeliefState = None
return state
def Valid(self, pos):
if self.Grid.Inside(pos) and pos not in self.Occlusions:
return True
return False
def NextPos(self, fromCoord, dir):
nextPos = fromCoord + Compass[dir]
if self.Valid(nextPos):
return nextPos
else:
return Compass[COMPASS.NAA]
def Step(self, state, action):
reward = self.RewardDefault
state.AgentDir = action
newpos = self.NextPos(state.AgentPos, action)
if self.Valid(newpos):
state.AgentPos = newpos
else:
reward += self.RewardHitWall
observation = 0
hitPredator = 0
if state.AgentPos == state.PredatorPos:
reward += self.RewardDie
return True, state, observation, reward # Terminate death
if self.PredatorObservation(state):
state.PredatorBeliefState = [state.AgentPos]
if not self.PredatorObservation(state):
state.PredatorBeliefState = self.PredatorAgentPosPropogation(state)
previousPredatorLocation = state.PredatorPos
state, hitPredator = self.MovePredator(state,
Bernoulli(self.MoveProbability),
previousPredatorLocation)
observation = self.MakeObservation(state, action)
if hitPredator:
reward += self.RewardDie
return True, state, observation, reward #Terminate death
if state.AgentPos == self.GoalPos:
reward += self.RewardClearLevel
return True, state, observation, reward #Terminate goal state
state.Depth += 1
return False, state, observation, reward
def MakeObservation(self, state, action):
observation = 0
if self.VisualRange:
visualArea = self.Grid.VisualArea(state.AgentPos, action,
self.VisualRange)
# Predator Observation
for i, coord in enumerate(visualArea):
if state.PredatorPos == coord:
if self.Grid.VisualRay((state.AgentPos).Copy(),
(coord).Copy(), self.Occlusions)[0]:
observation = i #SetFlag(observation, i)
else:
if self.Grid.VisualRay((state.AgentPos).Copy(),
(state.PredatorPos).Copy(),
self.Occlusions)[0]:
observation = 1
return observation
def PredatorObservation(self, state):
predatorObservation, _ = self.Grid.VisualRay(
(state.AgentPos).Copy(), (state.PredatorPos).Copy(),
self.Occlusions)
return predatorObservation
def PredatorAgentPosPropogation(self, state):
copyState = self.Copy(state)
N2 = 15
N1 = 15
allPossibleAgentNewPositions = [copyState.PredatorBeliefState[0]]
testedAgentPositions = []
for n1 in range(N1):
agentPosition = copyState.PredatorBeliefState[Random(
0, len(copyState.PredatorBeliefState))]
testedAgentPositions.append(agentPosition)
propogateState = self.Copy(copyState)
propogateState.AgentPos = agentPosition
if self.PredatorObservation(propogateState):
continue
newAgentPositions = []
for n2 in range(N2):
for action in range(self.NumActions):
newAgentPosition = self.NextPos(propogateState.AgentPos,
action)
if self.Valid(
newAgentPosition
) and newAgentPosition != copyState.PredatorPos:
newAgentPositions.append(newAgentPosition)
if newAgentPositions:
allPossibleAgentNewPositions.extend(newAgentPositions)
for agentCoord in copyState.PredatorBeliefState:
if agentCoord not in testedAgentPositions:
allPossibleAgentNewPositions.append(agentCoord)
return allPossibleAgentNewPositions
def LocalMove(self, state, history, stepObs, status):
allPredatorLocations = [
COORD(x, y) for x in range(self.XSize) for y in range(self.YSize)
]
possiblePredatorLocations = list(
set(allPredatorLocations) - set(self.Occlusions)
) #Remove occlusions from possible predator location list
state.PredatorPos = possiblePredatorLocations[Random(
0, len(possiblePredatorLocations))]
#state.PredatorPos = COORD(Random(0, self.Grid.GetXSize()),
# Random(0, self.Grid.GetYSize()))
if history.Size() == 0:
return True, state
observation = self.MakeObservation(state, state.AgentDir)
return history.Back().Observation == observation
def MovePredator(self, state, move, previousPredatorLocation):
numberOfMoves = 1
randomMove = True
believedState = self.Copy(state)
if move:
numberOfMoves = state.PredatorSpeedMult
if state.PredatorBeliefState:
try:
believedAgentPosition = state.PredatorBeliefState[0]
randomMove = False
except IndexError:
numberOfMoves = 1
pass
if len(state.PredatorBeliefState) > 1:
believedAgentPosition = state.PredatorBeliefState[Random(
0, len(state.PredatorBeliefState))]
numberOfMoves = 1
randomMove = False
believedState.AgentPos = believedAgentPosition
for i in range(numberOfMoves):
if Bernoulli(self.ChaseProbability) or i > 0 and not randomMove:
believedState = self.MovePredatorAggressive(
believedState, previousPredatorLocation)
else:
believedState = self.MovePredatorRandom(believedState)
state.PredatorPos = believedState.PredatorPos
if state.AgentPos == state.PredatorPos:
return state, (state.AgentPos == state.PredatorPos)
return state, (state.AgentPos == state.PredatorPos)
def MovePredatorRandom(self, state):
copyState = self.Copy(state)
predatorPos = copyState.PredatorPos
testedActions = []
while True:
action = Random(0, 4)
testedActions.append(action)
newpos = self.NextPos(predatorPos, action)
if self.Valid(newpos):
break
if set(testedActions) == {0, 1, 2, 3}:
newpos = copyState.PredatorPos
break
copyState.PredatorPos = newpos
copyState.PredatorDir = action
return copyState
def MovePredatorAggressive(self, state, previousPredatorLocation):
newState = self.Copy(state)
bestDist = self.Grid.GetXSize() + self.Grid.GetYSize()
bestPos = state.PredatorPos
bestDir = -1
agentPos = state.AgentPos
predatorPos = state.PredatorPos
for dir in range(0, 4):
dist = AggressiveDirectionalDistance(agentPos, predatorPos, dir)
newpos = self.NextPos(predatorPos, dir)
if dist <= bestDist and self.Valid(
newpos) and newpos != previousPredatorLocation:
bestDist = dist
bestPos = newpos
bestDir = dir
newState.PredatorPos = bestPos
newState.PredatorDir = bestDir
return newState
def GenerateLegal(self, state, history, legal, status):
for a in range(self.NumActions):
newpos = self.NextPos(state.AgentPos, a)
if self.Valid(newpos) and newpos != state.PredatorPos:
legal.append(a)
return legal
def GeneratePreferred(self, state, history, actions, status):
if history.Size():
for a in range(self.NumActions):
newpos = self.NextPos(state.AgentPos, a)
if self.Valid(newpos) and newpos != state.PredatorPos:
actions.append(a)
if Opposite(history.Back().Action) in actions:
actions.remove(Opposite(history.Back().Action))
#actions = self.GenerateExplorationActions(state, history, actions, status)
return actions
else:
return self.GenerateLegal(state, history, actions, status)
def DisplayBeliefs(self, beliefState):
counts = [0] * (self.Grid.GetYSize() * self.Grid.GetXSize())
for i in range(beliefState.GetNumSamples()):
state = beliefState.GetSample(i)
predatorIndex = self.Grid.Index(state.PredatorPos.X,
state.PredatorPos.Y)
counts[predatorIndex] += 1
counts = np.reshape(np.array(counts, dtype=np.float32),
(self.Grid.GetXSize(), self.Grid.GetYSize()))
for x in range(self.Grid.GetYSize()):
for y in range(self.Grid.GetXSize()):
counts[x, y] = float(counts[x, y]) / float(
beliefState.GetNumSamples())
print("Belief State: ", counts)
def DisplayAction(self, state, action):
print("Agent moves ", CompassString[action])
