def _passBall(self, pointToPassTo):
'''
If a keeper currently has the ball, then it has the option to hold the ball,
or pass it. Call this function to pass the ball. pointToPassTo is the coordinate that
the keeper can pass to. these are pixel values
:param pointToPassTo: the tile that the agent is passing to. It is an XY coordinate defined to be the top left
corner of the tile you're trying to pass to
:type pointToPassTo: typle of int
:returns: no return
'''
if self.fieldBall == None:
print("ERROR: trying to hold ball without actually having ball")
return
#pass to team mate integerK. if integerK = 1, then it's the 2nd element in array
selfToTargetDirection = kUtil.unitVector(kUtil.getVector(self.__getBallCenter(self.noisyBallPos), pointToPassTo))
selfToTargetVector = (kUtil.scalarMultiply(self.fieldBall.maxBallSpeed, selfToTargetDirection))
#at this point, you've determined the angle you wanna pass, and you pass.
#set ball's possesion to false, and update to new point. ball class handles direction vector
self.fieldBall.updatePosession(False)
self.inPosession = False
self.isKicking = True
#kUtil.addVectorToPoint(self.fieldBall.trueBallPos, selfToTeammateVector)
self.fieldBall.updateDirection(kUtil.getNoisyVals(selfToTargetVector, self.getSigma()))
def update(self, newDirectionVector):
if not self.inPosession:
#if no one's posessing it, then it's moving somewhere
self.trueBallDirection = kUtil.unitVector(newDirectionVector)
else:
#ball ain't goin nowhere if someone's posessing it
self.trueBallDirection = (0.0,0.0)
def __getRotatedVectors(self, vector, cos_k):
"""
FUNCTION NOT USED IN FINAL IMPLEMENTATION
This function will calculate 2 other angles that the agent can kick the ball to. If
the agent has calculated a direct path from itself to another keeper, that should be
the input vector. If the agent is interested in passing at a 5 degree angle, then
the 2nd input should be the cosine of 5 degrees. This function will then calculate
and return the 2 unit vectors which are the vectors pointing at 5 degree angles
:param vector: the vector that points directly from the ball's noisy
position to the noisy position of the keeper the agent wants to pass to
:param cos_k: the cosine of the angle that the agent wants to pass at. The
reason cosine is used instead of the angle is for computational efficiency
:type vector: list or tuple of numbers
:type cos_k: number
:returns: a list of 2 unit vectors, each one representing the 2 directions that
the ball can be kicked to achieve the desired angle.
:rtype: list of tuples, each tuple being a tuple of floats.
"""
discriminantIsZero = False
terminalPosCosZero = kUtil.addVectorToPoint(self.noisyBallPos, vector)
vector = kUtil.unitVector(vector)
ax = vector[1] #columns are x
ay = vector[0] #rows are y
k = cos_k
term1 = 2*k*ax #term 1 = -b
discriminant = term1 * term1 - 4 * (ax*ax +ay*ay)*(-1.0*ay*ay + k * k)
discriminant = math.sqrt(discriminant)
if (abs(discriminant) < 0.00001):
discriminantIsZero = True
#denominator = 2 * (ax*ax + ay*ay) #should be 2 every time if A is a unit vector
denominator = 2 #should be 2 every time if A is a unit vector
bx1 = (term1 - discriminant) / denominator
#print "term1: ", term1, " discriminant:", discriminant, " denominator: ", denominator
by1 = math.sqrt(1.0 - (bx1 * bx1))
returnUnitVectors = []
#make it (row,col) format, so therefore it's (y,x)
returnUnitVectors.append((by1, bx1))
returnUnitVectors.append((-1.0 * by1, bx1))
if discriminantIsZero == False:
bx2 = (term1 + discriminant) / denominator
by2 = math.sqrt(1.0 - (bx2 * bx2))
returnUnitVectors.append((by2, bx2))
returnUnitVectors.append((-1.0 * by2, bx2))
#print "return vectors"
#print returnVectors
returnUnitVectors = sorted(returnUnitVectors, key=lambda x: kUtil.getSqrDist(terminalPosCosZero, x))
return returnUnitVectors[:2]
def moveAttempt(self, inputAgent, reversedPolarCoord ):
noiseFreeDirectionVector = reversedPolarCoord[0]
distance = reversedPolarCoord[1]
#for the purposes of finding legal moves, just assume that they player is trying
#to cover the most amount of distance. Also, right now, it's not important if
#noiseFreeDirectionVector is a unit vector or not
quad = self.getQuadAttemptingToMoveTo(inputAgent, noiseFreeDirectionVector)
setOfLegalQuads = self.getLegalQuadrants(inputAgent)
#print(setOfLegalQuads)
#print("quad:", quad)
if quad in setOfLegalQuads:
#move is legal, do it
self.moveAgent(inputAgent, kUtil.scalarMultiply ( distance, kUtil.unitVector(noiseFreeDirectionVector)))
else:
#move is illegal. Simply return without calling or updating anything
#print("Illegal move: ", reversedPolarCoord)
return
def calcOptimal(self, agentList, i, intersect):
V = kUtil.getVector(self.fieldBall.trueBallPos, intersect)
UV = kUtil.unitVector(V)
stepVector = kUtil.scalarMultiply(self.maxBallSpeed, UV)
#keep adding the step vector to the optimal point
optimalPoint = self.fieldBall.trueBallPos
maxNumSteps = int(kUtil.getDist(self.fieldBall.trueBallPos, intersect)/ self.maxBallSpeed)
stepCount = 0
for k in range(maxNumSteps):
optimalPoint = kUtil.addVectorToPoint(optimalPoint, stepVector)
stepCount += 1
currPd = kUtil.getDist(optimalPoint,agentList[i].true_pos)
currBd = kUtil.getDist(self.fieldBall.trueBallPos, optimalPoint)
currPt = currPd / self.maxPlayerSpeed
currBt = currBd / self.maxBallSpeed
if currPt < currBt:
#found the optimal, so return it
return optimalPoint
#if you get here, then no closer optimal was found, so just return the intersect
return intersect
def moveAttempt(self, inputAgent, reversedPolarCoord ): """ This function is used by the agent in order to attempt movement on the field. If the move is legal, the agent's position is updated. If the move is illegal, then nothing happens. A move is illegal if the agent tries to go outside the boundaries of the field. :param inputAgent: a reference to the agent that is attempting to move :param reversedPolarCoord: the movement that the agent is trying to do. the movement is represented as a tuple where the first element is a unit vector representing the direction the agent is trying to move, and the 2nd element is the distance the agent is trying to move. :type inputAgent: agent :type reversedPolarCoord: tuple where first element is a tuple of floats, and the 2nd element is a float or integer :returns: true if move was successful, false if not :rtype: boolean """ noiseFreeDirectionVector = reversedPolarCoord[0] distance = reversedPolarCoord[1] #for the purposes of finding legal moves, just assume that they player is trying #to cover the most amount of distance. Also, right now, it's not important if #noiseFreeDirectionVector is a unit vector or not quad = self.__getQuadAttemptingToMoveTo(inputAgent, noiseFreeDirectionVector) setOfLegalQuads = self.__getLegalQuadrants(inputAgent) #print setOfLegalQuads #print "quad:", quad if quad in setOfLegalQuads: #move is legal, do it self.__moveAgent(inputAgent, kUtil.scalarMultiply ( distance, kUtil.unitVector(noiseFreeDirectionVector))) else: #move is illegal. Simply return without calling or updating anything #print "Illegal move: ", reversedPolarCoord return False if kUtil.magnitude(noiseFreeDirectionVector) == 0.0: return False else: return True
def passBall(self, integerK):
#if you're passing to integerK = 1, then that means pass to the keeper that's closer to you
#if you're passing ot integerK = 2, then that means pass to the keeper that's farther to you
#0 is an invalid input
sortedKeepers = sorted(self.keeperArray)
if integerK == 0:
print("Invalid input for integerK! integerK not allowed to be", integerK)
return
if self.fieldBall == None:
print("ERROR: trying to hold ball without actually having ball")
return
#pass to team mate integerK. if integerK = 1, then it's the 2nd element in array
selfToTeammateDirection = kUtil.unitVector(kUtil.getVector(self.noisyBallPos, sortedKeepers[integerK].noisy_pos))
selfToTeammateVector = (kUtil.scalarMultiply(self.fieldBall.maxBallSpeed, selfToTeammateDirection))
#set ball's possesion to false, and update to new point. ball class handles direction vector
self.fieldBall.updatePosession(False)
self.inPosession = False
self.isKicking = True
#kUtil.addVectorToPoint(self.fieldBall.trueBallPos, selfToTeammateVector)
self.fieldBall.update(selfToTeammateVector)
#self.fieldBall.updatepos( kUtil.addVectorToPoint(self.fieldBall.true_pos, selfToTeammateVector ) )
return (selfToTeammateDirection, self.maxBallSpeed)
def updateDirection(self, newDirectionVector):
"""
update the direction component of ball velocity
This function is called upon by the agent class to attempt an
update to update the direction that the ball is going. The direction
is stored as a unit vector.
:param newDirectionVector: a tuple representing the direction
that the agent is trying to change the ball to. this vector
does not need to be in the form of a unit vector. The direction
will only be set if the ball is NOT in posession. If the ball is
in possession, the the direction will remain (0.0,0.0).
:type newDirectionVector: float, float
:returns: no return
"""
if not self.inPosession:
#if no one's posessing it, then it's moving somewhere
self.trueBallDirection = kUtil.unitVector(newDirectionVector)
else:
#ball ain't goin nowhere if someone's posessing it
self.trueBallDirection = (0.0,0.0)
def _passBall(self, integerK):
"""
If a keeper currently has the ball, then it has the option to hold the ball,
or pass it. Call this function to pass the ball. integerK represents the
keeper that the ball holder is passing to. integerK = 1 means pass to the
keeper that is closest to the ball besides the ball holder. integerK = 2
means pass to the 2nd closest, and so on. Only subclasses of agent should
be calling this function.
:param integerK: this represents the
keeper that the ball holder is passing to. integerK = 1 means pass to the
keeper that is closest to the ball besides the ball holder. integerK = 2
means pass to the 2nd closest, and so on.
:type integerK: integer
:returns: no return
"""
#print("passing to keeper " + str(integerK) + ", indexed by distance. ")
#if you're passing to integerK = 1, then that means pass to the keeper that's closer to you
#if you're passing ot integerK = 2, then that means pass to the keeper that's farther to you
#0 is an invalid input
sortedKeepers = sorted(self.keeperArray)
if integerK == 0:
print("Invalid input for integerK! integerK not allowed to be", integerK)
return
if self.fieldBall == None:
print("ERROR: trying to hold ball without actually having ball")
return
#pass to team mate integerK. if integerK = 1, then it's the 2nd element in array
selfToTeammateDirection = kUtil.unitVector(kUtil.getVector(self.noisyBallPos, sortedKeepers[integerK].get_noisy_pos()))
selfToTeammateVector = (kUtil.scalarMultiply(self.fieldBall.maxBallSpeed, selfToTeammateDirection))
"""
#this code segment is for determining which angle you'd rather pass to. it's all deterministic
ballPos = self.noisyBallPos
passVectorsToConsider = []
passVectorsToConsider.append(selfToTeammateDirection)
for i in range(len(self.cosinesOfInterest)):
passVectorsToConsider = passVectorsToConsider + self.__getRotatedVectors(selfToTeammateDirection, self.cosinesOfInterest[i])
#now sort the vectors based on how open they are:
self.worldRef.debugPassVectors(ballPos, passVectorsToConsider)
passVectorsToConsider = sorted(passVectorsToConsider,
key = lambda vector: max ( kUtil.cosTheta(self.worldRef.takerArray[0].getNoisyMidPoint(), ballPos, kUtil.addVectorToPoint(ballPos, vector)),
kUtil.cosTheta(self.worldRef.takerArray[1].getNoisyMidPoint(), ballPos, kUtil.addVectorToPoint(ballPos, vector))),
)
#iterate over the sorted list until you find a pass that you can do
for i in range(len(passVectorsToConsider)):
if( calcReceive.calc_receive(self.worldRef, passVectorsToConsider[i]) != None):
selfToTeammateDirection = passVectorsToConsider[i]
selfToTeammateVector = (kUtil.scalarMultiply(self.fieldBall.maxBallSpeed, selfToTeammateDirection))
print "PASS USING ANGLE ACHEIVED AT i=", i
break
"""
#at this point, you've determined the angle you wanna pass, and you pass.
#set ball's possesion to false, and update to new point. ball class handles direction vector
self.fieldBall.updatePosession(False)
self.inPosession = False
self.isKicking = True
#kUtil.addVectorToPoint(self.fieldBall.trueBallPos, selfToTeammateVector)
self.fieldBall.updateDirection(kUtil.getNoisyVals(selfToTeammateVector, self.__sigma))
def __calcOptimal(worldRef, agentList, i, intersect):
"""
This function is a private function meant to assist another private function called
__calc_receive_ball_moving.
once __calc_receive_ball_moving has calculated the intersection point, there's
one last step: to make sure that the intersection point isn't too close to
the out of bounds area. If the intersection point too close to out of bounds,
then return an intersection point along the path that the ball is traveling, but
is just still safely away from the out of bounds areas.
.. note::
This is a private function that the user shouldn't worry about calling.
Only the calc_receive function should be called.
:param worldRef: a reference to the simulator class which is calling this function
:param agentList: a list provided by the simulator of all agents
:param i: the index of the agent running to the ball for the list agentList
:param intersect: the intersection point that has been calculated, and might be too
close to out of bounds
:type worldRef: keepAway class
:type agentList: a list where each element is an agent class
:type i: integer
:type intersect: a tuple of floats
:returns: the intersection coordinate which is safely within bounds, or the original
intersection point if no such point is found
:rtype: tuple of floats
"""
#if the intersect is in bounds, just go to it. no calculations needed
if __isPointOutOfPlayRegion(worldRef, intersect, agentList, i) == False:
#print("point in bounds, return intersect")
return intersect
#V = vector from agent's perpendicular intercept to the ball
V = kUtil.getVector(intersect, worldRef.fieldBall.trueBallPos)
#turn V into a unit vector and multipy it by the speed of the ball to get velocity vector
UV = kUtil.unitVector(V)
stepVector = kUtil.scalarMultiply(worldRef.maxBallSpeed, UV)
#the optimal point is intialized to the intersect, and
#the intersect is currently out of bounds.
#keep adding the step vector to the optimal point until
#the intersect is no longer out of bounds
optimalPoint = intersect
maxNumSteps = int(kUtil.getDist(worldRef.fieldBall.trueBallPos, intersect)/ worldRef.maxBallSpeed)
stepCount = 0
#if you can't get to the ball in maxNumSteps, then it's hopeless. simply
#return the intersection point. Your agent will fail and the ball will
#go out of bounds, but there's nothing that can be done
for k in range(maxNumSteps):
optimalPoint = kUtil.addVectorToPoint(optimalPoint, stepVector)
stepCount += 1
if __isPointOutOfPlayRegion(worldRef, optimalPoint, agentList, i) == False:
#print("Optimal found, returning optimal point:", optimalPoint)
return optimalPoint
#if you get here, then no closer optimal was found
#print("no optimal found, returning intersect", intersect)
return intersect
def commonFunctionality(self, mode, showDisplay = True, turnOnGrid = False, prettyGrid = False): #this is common code that will occur regardless of what agent you picked #if (self.fieldBall.inPosession == False): newBallPoint = kUtil.addVectorToPoint(self.fieldBall.trueBallPos, kUtil.scalarMultiply(self.maxBallSpeed, kUtil.unitVector(self.fieldBall.trueBallDirection))) self.fieldBall.updateCoordinate(newBallPoint) for i in range(len(self.takerArray)): self.takerArray[i].noisyBallPos = kUtil.getNoisyVals(self.fieldBall.trueBallPos, self.takerArray[i].getSigma()) for i in range(len(self.keeperArray)): self.keeperArray[i].noisyBallPos = kUtil.getNoisyVals(self.fieldBall.trueBallPos, self.keeperArray[i].getSigma()) self.__updateBallPosession() self.__updateScore() #remove this line if you don't want the grid to be drawn if showDisplay: if (turnOnGrid): gridList = self.bev.getBirdsEyeViewAsList(self.keeperArray, self.takerArray) substrate = self.bev.getSubstrate(self.keeperArray, self.takerArray) self.__drawWorld (mode, gridList, substrate, prettyGrid) else: self.__drawWorld(mode) self.__displayScore() pygame.display.update()
def gameLoop(self, mode):
"""
This is the main game loop. Each iteration of this counts as a tick.
With each tick, an agent can move keepAway.maxPlayerSpeed units, and the
ball can move keepAway.maxBallSpeed units. At the end of each tick, the
pygame screen is updated to the next frame.
:returns: no return
"""
self.__drawWorld()
gameExit = False
pygame.display.update()
experimentAgent = self.keeperArray[0]
# each occurance of this loop is treated as one simulation cycle
while not gameExit:
if mode == "manual":
for event in pygame.event.get():
if event.type == pygame.QUIT:
gameExit = True
if event.type == pygame.KEYDOWN:
if event.key == pygame.K_LEFT:
self.moveAttempt(experimentAgent, ((0, -1), self.maxPlayerSpeed))
elif event.key == pygame.K_RIGHT:
self.moveAttempt(experimentAgent, ((0, 1), self.maxPlayerSpeed))
elif event.key == pygame.K_UP:
self.moveAttempt(experimentAgent, ((-1, 0), self.maxPlayerSpeed))
elif event.key == pygame.K_DOWN:
self.moveAttempt(experimentAgent, ((1, 0), self.maxPlayerSpeed))
elif event.key == pygame.K_1:
self.moveAttempt(experimentAgent, ((-1, -1), self.maxPlayerSpeed))
elif event.key == pygame.K_2:
self.moveAttempt(experimentAgent, ((-1, 1), self.maxPlayerSpeed))
elif event.key == pygame.K_3:
self.moveAttempt(experimentAgent, ((1, -1), self.maxPlayerSpeed))
elif event.key == pygame.K_4:
self.moveAttempt(experimentAgent, ((1, 1), self.maxPlayerSpeed))
elif mode == "hand_coded":
for event in pygame.event.get():
if event.type == pygame.QUIT:
gameExit = True
self.sendCalcReceiveDecision()
self.sendSimpleStateVars()
for keeper in self.keeperArray:
keeper.decisionFlowChart()
for taker in self.takerArray:
taker.decisionFlowChart()
elif mode == "sarsa":
for event in pygame.event.get():
if event.type == pygame.QUIT:
gameExit = True
self.sendCalcReceiveDecision()
self.sendSimpleStateVars()
# this is common code that will occur regardless of what agent you picked
# if (self.fieldBall.inPosession == False):
newBallPoint = kUtil.addVectorToPoint(
self.fieldBall.trueBallPos,
kUtil.scalarMultiply(self.maxBallSpeed, kUtil.unitVector(self.fieldBall.trueBallDirection)),
)
self.fieldBall.updateCoordinate(newBallPoint)
for i in range(len(self.takerArray)):
self.takerArray[i].noisyBallPos = kUtil.getNoisyVals(
self.fieldBall.trueBallPos, self.takerArray[i].getSigma()
)
for i in range(len(self.keeperArray)):
self.keeperArray[i].noisyBallPos = kUtil.getNoisyVals(
self.fieldBall.trueBallPos, self.keeperArray[i].getSigma()
)
self.__updateBallPosession()
self.__updateScore()
self.__drawWorld()
self.__displayScore()
pygame.display.update()
if self.isGameOver() == True:
gameExit = True
print("final score: ", self.keeperScore)
# this specifies frames per second
self.clock.tick(self.test_fps)
self.__finish()
# self.pause("Game Over: Final Score %d" % self.keeperScore)
self.__exitSim()
def gameLoop(self, mode):
self.drawWorld ()
gameExit = False
if(self.displayGraphics == True):
pygame.display.update()
experimentAgent = self.takerArray[0]
#each occurance of this loop is treated as one simulation cycle
while not gameExit:
if(mode == "manual"):
for event in pygame.event.get():
if event.type == pygame.QUIT:
gameExit = True
if event.type == pygame.KEYDOWN:
if event.key == pygame.K_LEFT:
self.moveAttempt(experimentAgent, ((0,-1), self.maxPlayerSpeed))
elif event.key == pygame.K_RIGHT:
self.moveAttempt(experimentAgent, ((0,1), self.maxPlayerSpeed))
elif event.key == pygame.K_UP:
self.moveAttempt(experimentAgent, ((-1,0), self.maxPlayerSpeed))
elif event.key == pygame.K_DOWN:
self.moveAttempt(experimentAgent, ((1,0), self.maxPlayerSpeed))
elif event.key == pygame.K_1:
self.moveAttempt(experimentAgent, ((-1,-1), self.maxPlayerSpeed))
elif event.key == pygame.K_2:
self.moveAttempt(experimentAgent, ((-1,1), self.maxPlayerSpeed))
elif event.key == pygame.K_3:
self.moveAttempt(experimentAgent, ((1,-1), self.maxPlayerSpeed))
elif event.key == pygame.K_4:
self.moveAttempt(experimentAgent, ((1,1), self.maxPlayerSpeed))
elif (mode == "hand_coded"):
for event in pygame.event.get():
if event.type == pygame.QUIT:
gameExit = True
self.sendStateVars()
self.calc_receive()
for keeper in self.keeperArray:
keeper.decisionFlowChart()
for taker in self.takerArray:
taker.decisionFlowChart()
elif(mode == "q_learning"):
totalTraining = 5
flag = False
for index in range(len(self.keeperArray)):
if self.keeperArray[index].load_obj("dict",index, mode) == None:
flag = True
if flag:
print("no files exist")
self.QTraining(totalTraining)
for index in range(len(self.keeperArray)):
self.keeperArray[index].save_obj(self.keeperArray[index].q_values,"dict",index, mode)
#for key in list(self.keeperArray[index].q_values.keys())[:10]:
#print("QValues of ",index," agent is: key=",key," value=",self.keeperArray[index].q_values[key])
self.Qtesting()
else:
print("files exist, continue training")
totalTraining = 0
for index in range(len(self.keeperArray)):
self.keeperArray[index].q_values = self.keeperArray[index].load_obj("dict",index, mode)
#for key in list(self.keeperArray[index].q_values.keys())[:10]:
#print("QValues of ",index," agent is: key=",key," value=",self.keeperArray[index].q_values[key])
self.QTraining(totalTraining)
for index in range(len(self.keeperArray)):
self.keeperArray[index].save_obj(self.keeperArray[index].q_values,"dict",index, mode)
self.Qtesting()
elif(mode == "sarsa"):
totalTraining = 5
flag = False
for index in range(len(self.keeperArray)):
if self.keeperArray[index].load_obj("dict",index, mode) == None:
flag = True
if flag:
print("no files exist")
self.QTraining(totalTraining)
for index in range(len(self.keeperArray)):
self.keeperArray[index].save_obj(self.keeperArray[index].q_values,"dict",index, mode)
#for key in list(self.keeperArray[index].q_values.keys())[:10]:
#print("QValues of ",index," agent is: key=",key," value=",self.keeperArray[index].q_values[key])
self.Qtesting()
else:
print("files exist, continue training")
totalTraining = 0
for index in range(len(self.keeperArray)):
self.keeperArray[index].q_values = self.keeperArray[index].load_obj("dict",index, mode)
#for key in list(self.keeperArray[index].q_values.keys())[:10]:
#print("QValues of ",index," agent is: key=",key," value=",self.keeperArray[index].q_values[key])
self.QTraining(totalTraining)
for index in range(len(self.keeperArray)):
self.keeperArray[index].save_obj(self.keeperArray[index].q_values,"dict",index, mode)
self.Qtesting()
#this is common code that will occur regardless of what agent you picked
#if (self.fieldBall.inPosession == False):
newBallPoint = kUtil.addVectorToPoint(self.fieldBall.trueBallPos, kUtil.scalarMultiply(self.maxBallSpeed, kUtil.unitVector(self.fieldBall.trueBallDirection)))
self.fieldBall.updateCoordinate(newBallPoint)
for i in range(len(self.takerArray)):
self.takerArray[i].noisyBallPos = kUtil.getNoisyVals(self.fieldBall.trueBallPos, self.takerArray[i].sigma)
for i in range(len(self.keeperArray)):
self.keeperArray[i].noisyBallPos = kUtil.getNoisyVals(self.fieldBall.trueBallPos, self.keeperArray[i].sigma)
self.updateBallPosession()
self.updateScore()
self.drawWorld ()
self.displayScore()
pygame.display.update()
if self.isGameOver() == True:
gameExit = True
print("final score: ", self.keeperScore)
#this specifies frames per second
self.clock.tick(self.fps)
self.finish()
#self.pause("Game Over: Final Score %d" % self.keeperScore)
self.exitSim()
def Qtesting(self):
self.resetGameForTraining()
while self.isGameOver() == False:
for event in pygame.event.get():
if event.type == pygame.QUIT:
gameExit = True
self.sendStateVars()
self.calc_receive()
for keeper in self.keeperArray:
keeper.isInTraining = False
keeper.decisionFlowChart()
for taker in self.takerArray:
taker.decisionFlowChart()
newBallPoint = kUtil.addVectorToPoint(self.fieldBall.trueBallPos, kUtil.scalarMultiply(self.maxBallSpeed, kUtil.unitVector(self.fieldBall.trueBallDirection)))
self.fieldBall.updateCoordinate(newBallPoint)
for i in range(len(self.takerArray)):
self.takerArray[i].noisyBallPos = kUtil.getNoisyVals(self.fieldBall.trueBallPos, self.takerArray[i].sigma)
for i in range(len(self.keeperArray)):
self.keeperArray[i].noisyBallPos = kUtil.getNoisyVals(self.fieldBall.trueBallPos, self.keeperArray[i].sigma)
self.updateBallPosession()
self.updateScore()
self.drawWorld ()
self.displayScore()
pygame.display.update()
#this specifies frames per second
self.clock.tick(self.fps)
if self.isGameOver() == True:
gameExit = True
print("final score: ", self.keeperScore)
self.finish()
#self.pause("Game Over: Final Score %d" % self.keeperScore)
self.exitSim()
def QTraining(self,totalTraining):
for training in range(totalTraining):
print("Training number :",training)
if training%100 == 0:
self.displayGraphics = True
else:
self.displayGraphics = False
self.resetGameForTraining()
while self.isGameOver() == False:
for event in pygame.event.get():
if event.type == pygame.QUIT:
gameExit = True
self.sendStateVars()
reward = 100000
for keeper in self.keeperArray:
keeper.updateReward(reward)
self.calc_receive()
for keeper in self.keeperArray:
keeper.isInTraining = True
keeper.decisionFlowChart()
for taker in self.takerArray:
taker.decisionFlowChart()
newBallPoint = kUtil.addVectorToPoint(self.fieldBall.trueBallPos, kUtil.scalarMultiply(self.maxBallSpeed, kUtil.unitVector(self.fieldBall.trueBallDirection)))
self.fieldBall.updateCoordinate(newBallPoint)
for i in range(len(self.takerArray)):
self.takerArray[i].noisyBallPos = kUtil.getNoisyVals(self.fieldBall.trueBallPos, self.takerArray[i].sigma)
for i in range(len(self.keeperArray)):
self.keeperArray[i].noisyBallPos = kUtil.getNoisyVals(self.fieldBall.trueBallPos, self.keeperArray[i].sigma)
self.updateBallPosession()
self.updateScore()
if(self.displayGraphics == True):
self.drawWorld ()
self.displayScore()
pygame.display.update()
if self.isGameOver():
reward = -100
self.sendStateVars()
for keeper in self.keeperArray:
keeper.updateFinalReward(reward)
self.clock.tick(10000)