def AI_loop():
#Release keys
ai.thrust(0)
ai.turnLeft(0)
ai.turnRight(0)
#Set variables
heading = int(ai.selfHeadingDeg())
tracking = int(ai.selfTrackingDeg())
frontWall = ai.wallFeeler(500, heading)
left45Wall = ai.wallFeeler(500, heading + 45)
right45Wall = ai.wallFeeler(500, heading - 45)
left90Wall = ai.wallFeeler(500, heading + 90)
right90Wall = ai.wallFeeler(500, heading - 90)
left135Wall = ai.wallFeeler(500, heading + 135)
right135Wall = ai.wallFeeler(500, heading - 135)
backWall = ai.wallFeeler(500, heading - 180)
trackWall = ai.wallFeeler(500, tracking)
####### Shooting Ennemies ########
##Find the closest ennemy##
ClosestID = ai.closestShipId()
#print(ClosestID)
##Get the closest ennemy direction and speed##
ClosestSpeed = ai.enemySpeedId(ClosestID)
#print(ClosestSpeed)
ClosestDir = ai.enemyTrackingDegId(ClosestID)
#print(ClosestDir)
## Get the lockheadingdeg ##
enemy = ai.lockNext()
print(enemy)
head = ai.lockHeadingDeg()
print(head)
enemyDist = ai.selfLockDist()
print(enemyDist)
### Turning Rules ###
if frontWall <= 200 and (left45Wall < right45Wall):
print("turning right")
ai.turnRight(1)
elif frontWall <= 200 and (left45Wall > right45Wall):
ai.turnLeft(1)
elif left90Wall <= 200:
print("turning right")
ai.turnRight(1)
elif right90Wall <= 200:
print("turning left")
ai.turnLeft(1)
### Thrust commands ####
elif ai.selfSpeed() <= 10 and (frontWall >= 200) and (
left45Wall >= 200) and (right45Wall >= 200) and (
right90Wall >= 200) and (left90Wall >= 200) and (
left135Wall >= 50) and (right135Wall >= 50) and (backWall
>= 50):
print("go forward")
ai.thrust(1)
elif trackWall < 75 and ai.selfSpeed() >= 10:
ai.thrust(1)
elif trackWall < 50 and ai.selfSpeed() <= 10:
ai.thrust(1)
elif backWall <= 75:
ai.thrust(1)
elif left135Wall <= 75:
ai.thrust(1)
elif right135Wall <= 75:
ai.thrust(1)
##### Shooting Ennemy Commands #####
elif enemyDist <= 500 and heading > (head):
ai.turnRight(1)
ai.fireShot()
elif enemyDist <= 500 and heading < (head):
ai.turnLeft(1)
ai.fireShot()
else:
print("chilling")
ai.thrust(0)
def AI_loop():
global count_frame, loop, boolean, score, population_size, chromosome_size, population, mutation_prob, crossover_prob, fitness_list, generation, generation_size, first_time, done_learning
#Release keys
ai.thrust(0)
ai.turnLeft(0)
ai.turnRight(0)
## Get A Chromosome in the Population -- Eventually Will go through each individual in the population ##
current_chromosome = population[loop]
## Transform Each Gene insisde A Single Selected Chromosome. 0s & 1s Are Turned Into Intergers For Fuzzy Sets to understand ##
## Each Value obtained is used to calculate the risk of each 45 degree around the agent ##
## Each value has its own "jump" variable which refers to the distance from each possible points/values ##
## The start and end represents the possible start point and end point for each variable and they depend on
## what the variiable is. It is to ensure a viable fuzzy set and fuzzy functions that these restrictions are applied. ##
closingRate_SlowTopAlert = current_chromosome[0:4]
closingRate_SlowTopAlertValue = transform_fuzzy(closingRate_SlowTopAlert,
1, 0, 16)
closingRate_MediumTopLeftAlert = current_chromosome[4:8]
closingRate_MediumTopLeftAlertValue = transform_fuzzy(
closingRate_MediumTopLeftAlert, 1, (closingRate_SlowTopAlertValue + 1),
(closingRate_SlowTopAlertValue + 1) + 16)
closingRate_MediumTopRightAlert = current_chromosome[8:12]
closingRate_MediumTopRightAlertValue = transform_fuzzy(
closingRate_MediumTopRightAlert, 1,
(closingRate_MediumTopLeftAlertValue + 1),
(closingRate_MediumTopLeftAlertValue + 1) + 16)
closingRate_FastTopAlert = current_chromosome[12:16]
closingRate_FastTopAlertValue = transform_fuzzy(
closingRate_FastTopAlert, 1,
(closingRate_MediumTopRightAlertValue + 1),
(closingRate_MediumTopRightAlertValue + 1) + 16)
closingRate_SlowBottomAlert = current_chromosome[16:20]
start = (closingRate_SlowTopAlertValue +
(((closingRate_MediumTopLeftAlertValue -
closingRate_SlowTopAlertValue) // 2) + 1))
end = (start + (1 * (2**(len(closingRate_SlowBottomAlert)))))
closingRate_SlowBottomAlertValue = transform_fuzzy(
closingRate_SlowBottomAlert, 1, start, end)
closingRate_MediumBottomLeftAlert = current_chromosome[20:24]
end = (closingRate_MediumTopLeftAlertValue -
(((closingRate_MediumTopLeftAlertValue -
closingRate_SlowTopAlertValue) // 2) + 1))
start = end - (1 * (2**(len(closingRate_MediumBottomLeftAlert))))
if (end < 0):
end = 0
if (start < 0):
start = 0
jump = (end - start) // (2**(len(closingRate_MediumBottomLeftAlert)))
closingRate_MediumBottomLeftAlertValue = transform_fuzzy(
closingRate_MediumBottomLeftAlert, jump, start, end)
closingRate_MediumBottomRightAlert = current_chromosome[24:28]
start = (closingRate_MediumTopRightAlertValue +
(((closingRate_FastTopAlertValue -
closingRate_MediumTopRightAlertValue) // 2) + 1))
end = start + (1 * (2**(len(closingRate_MediumBottomRightAlert))))
closingRate_MediumBottomRightAlertValue = transform_fuzzy(
closingRate_MediumBottomRightAlert, 1, start, end)
closingRate_FastBottomAlert = current_chromosome[28:32]
end = (closingRate_FastTopAlertValue -
(((closingRate_FastTopAlertValue -
closingRate_MediumTopRightAlertValue) // 2) + 1))
start = end - (1 * (2**(len(closingRate_FastBottomAlert))))
if (end < 0):
end = 0
if (start < 0):
start = 0
jump = (end - start) // (2**(len(closingRate_FastBottomAlert)))
closingRate_FastBottomAlertValue = transform_fuzzy(
closingRate_FastBottomAlert, jump, start, end)
Distance_CloseTopAlert = current_chromosome[32:37]
Distance_CloseTopAlertValue = transform_fuzzy(
Distance_CloseTopAlert, 50, 0, (50 * (2**len(Distance_CloseTopAlert))))
Distance_FarTopAlert = current_chromosome[37:42]
Distance_FarTopAlertValue = transform_fuzzy(
Distance_CloseTopAlert, 50, (Distance_CloseTopAlertValue + 50),
(Distance_CloseTopAlertValue + 50) +
(50 * (2**len(Distance_CloseTopAlert))))
Distance_CloseBottomAlert = current_chromosome[42:47]
start = (Distance_CloseTopAlertValue + ((
(Distance_FarTopAlertValue - Distance_CloseTopAlertValue) // 2) + 1))
end = Distance_FarTopAlertValue
jump = (end - start) // (2**(len(Distance_CloseBottomAlert)))
Distance_CloseBottomAlertValue = transform_fuzzy(Distance_CloseBottomAlert,
jump, start, end)
Distance_FarBottomAlert = current_chromosome[47:52]
end = (Distance_FarTopAlertValue - ((
(Distance_FarTopAlertValue - Distance_CloseTopAlertValue) // 2) + 1))
start = Distance_CloseTopAlertValue
jump = (end - start) // (2**(len(Distance_FarBottomAlert)))
Distance_FarBottomAlertValue = transform_fuzzy(Distance_FarBottomAlert,
jump, start, end)
#Set variables for Wall feelers, heading and tracking of the agent ##
heading = int(ai.selfHeadingDeg())
tracking = int(ai.selfTrackingDeg())
frontWall = ai.wallFeeler(500, heading)
left45Wall = ai.wallFeeler(500, heading + 45)
right45Wall = ai.wallFeeler(500, heading - 45)
left90Wall = ai.wallFeeler(500, heading + 90)
right90Wall = ai.wallFeeler(500, heading - 90)
left135Wall = ai.wallFeeler(500, heading + 135)
right135Wall = ai.wallFeeler(500, heading - 135)
backWall = ai.wallFeeler(500, heading - 180)
trackWall = ai.wallFeeler(500, tracking)
## Create an array that represents the closing rate of each 45 degree of the full 360 degrees surrounding the agent ##
result_list = []
## Array of the same size, but contains the risk of each direction ##
risk_list = []
for i in range(8):
Degree = tracking + (45 * i)
Speed = ai.selfSpeed()
Distance = ai.wallFeeler(10000, tracking + (45 * i))
result = Closing_Rate(Degree, tracking, Speed, Distance)
result_list.append(result)
### Calculate the Fuzzy membership ###
### 1. Fuzzy Membership For Closing Rate (Speed + Tracking Involved) ###
### 2. Fuzzy Membership For Distance From Walls ###
closing_rate, distance = Closing_Rate(Degree, tracking, Speed,
Distance)
low, medium, fast = Fuzzy_Speed(
closing_rate, closingRate_SlowTopAlertValue,
closingRate_SlowBottomAlertValue,
closingRate_MediumBottomLeftAlertValue,
closingRate_MediumTopLeftAlertValue,
closingRate_MediumTopRightAlertValue,
closingRate_MediumBottomRightAlertValue,
closingRate_FastBottomAlertValue, closingRate_FastTopAlertValue)
close, far = Fuzzy_Distance(distance, Distance_CloseTopAlertValue,
Distance_CloseBottomAlertValue,
Distance_FarBottomAlertValue,
Distance_FarTopAlertValue)
#print("close-far", close, far)
risk = Fuzzy_Risk(low, medium, fast, close, far)
risk_list.append(risk)
## Get the direction in deg that is most risky for the robot as well as the least risky direction ##
max_risk = max(risk_list)
track_risk = (tracking + (risk_list.index(max_risk) * 45) % 360)
min_risk = min(
risk_list
) ## Note: Biase Towards Left Side since min get the first min when risk might be equal ##
####### Getters Variable Regarding Important Information About Enemies ########
##Find the closest ennemy##
enemy = ai.lockClose()
## Get the lockheadingdeg of enemy ##
head = ai.lockHeadingDeg()
## Get the dstance from enemy ##
enemyDist = ai.selfLockDist()
## If the Enemy is Dead ##
if (ai.selfAlive() == 0 and boolean == False):
## Calculate Fitness Current Individual ##
score_previous = score
score_current = ai.selfScore()
fitness_value = fitness(population, count_frame, score_previous,
score_current)
fitness_list.append(fitness_value)
## If it went through the whole population and ready to move to next generation ##
if ((loop + 1) == population_size):
## Output the fitness of population to allow user to see if learning is happening ##
print("Generation:", generation)
print("Agent Fitness:")
print(fitness_list)
print("Average Fitness:", statistics.mean(fitness_list))
print("Best Fitness:", max(fitness_list))
## Finding the optimal chromosome to output it in data file ##
string_maxChromosome = ""
for chrom_max in range(chromosome_size):
string_maxChromosome = string_maxChromosome + str(
population[fitness_list.index(
max(fitness_list))][chrom_max])
## Formatting entire population in a big string to register it in excel file##
string_population = ""
for pop in range(population_size):
for pop_chrom in range(chromosome_size):
string_population = string_population + str(
population[pop][pop_chrom])
if (pop != (population_size - 1)):
string_population = string_population + ","
## Formatting entire population's fitness in a big string to register it in excel file##
string_fitness = ""
for fit in range(len(fitness_list)):
string_fitness = string_fitness + str(fitness_list[fit])
if (fit != (len(fitness_list) - 1)):
string_fitness = string_fitness + ","
## Output Data into Excel File ##
titles = [
"Generation", "Average Fitness", "Best Fitness",
"Population Size", "Chromosome Size", "Crossover Probability",
"Mutation Probability", "Best Chromosome",
"Entire Population Chromosome", "Entire Population Fitness"
]
data = [
generation,
statistics.mean(fitness_list),
max(fitness_list), population_size, chromosome_size,
crossover_prob, mutation_prob, string_maxChromosome,
string_population, string_fitness
]
first_time = Save_Data("Dumpster_Training_Data.xls", 0, titles,
data, first_time)
## Select Population For Next Generation -- Apply Crossover & Mutation ##
new_population = select(population, fitness_list)
new_population = crossover(new_population, chromosome_size,
population_size, crossover_prob)
new_population = mutate(new_population, chromosome_size,
mutation_prob)
population = new_population
loop = 0
count_frame = 0
generation += 1
fitness_list.clear()
### DONE -- QUIT ###
if (generation == generation_size):
quitAI()
## Move to the next individual in population ##
else:
loop += 1
count_frame = 0
boolean = True
else:
## The agent is Alive ##
if (ai.selfAlive() == 1):
## Get the angles on both side between tracking and heading to decide which way to turn ##
dist = (heading - track_risk) % 360
dist2 = (360 - dist) % 360
###### Production System Rules ######
## Turning Rules ##
if (dist <= 130 and dist >= 0 and ai.selfSpeed() > 0
and max_risk >= 75):
ai.turnLeft(1)
elif (dist2 <= 130 and dist2 >= 0 and ai.selfSpeed() > 0
and max_risk >= 75):
ai.turnRight(1)
elif (ai.selfSpeed() <= 10):
ai.thrust(1)
elif (trackWall <= 150):
ai.thrust(1)
##### Bullet Avoidance Commands #####
elif (ai.shotAlert(0) >= 0 and ai.shotAlert(0) <= 50):
if (ai.shotVelDir(0) != -1
and ai.angleDiff(heading, ai.shotVelDir(0)) > 0
and ai.selfSpeed() <= 5):
ai.turnLeft(1)
ai.thrust(1)
elif (ai.shotVelDir(0) != -1
and ai.angleDiff(heading, ai.shotVelDir(0)) < 0
and ai.selfSpeed() <= 5):
ai.turnRight(1)
ai.thrust(1)
elif (ai.shotVelDir(0) != -1
and ai.angleDiff(heading, ai.shotVelDir(0)) > 0
and ai.selfSpeed() > 5):
ai.turnLeft(1)
else:
ai.turnRight(1)
##### Shooting Ennemy Commands #####
elif (enemyDist <= 3000 and heading > (head) and enemyDist != 0
and ai.selfSpeed() > 5):
ai.turnRight(1)
ai.fireShot()
elif (enemyDist <= 3000 and heading < (head) and enemyDist != 0
and ai.selfSpeed() > 5):
ai.turnLeft(1)
ai.fireShot()
## Rules if nothing is happening ##
elif (ai.selfSpeed() < 5):
ai.thrust(1)
else:
ai.thrust(0)
count_frame += 3
boolean = False
def AI_loop():
turn, thrust = .5, 0
ai.turnLeft(0)
ai.turnRight(0)
ai.thrust(0)
ai.setTurnSpeed(64)
heading = int(ai.selfHeadingDeg())
tracking = int(ai.selfTrackingDeg())
trackWall = ai.wallFeeler(500, tracking)
trackL3 = ai.wallFeeler(500, tracking + 3)
trackL10 = ai.wallFeeler(500, tracking + 10)
trackR3 = ai.wallFeeler(500, tracking - 3)
trackR10 = ai.wallFeeler(500, tracking - 10)
frontWall = ai.wallFeeler(500, heading)
frontL = ai.wallFeeler(500, heading + 15)
frontR = ai.wallFeeler(500, heading - 15)
leftWall = ai.wallFeeler(500, heading + 90)
leftF = ai.wallFeeler(500, heading + 65)
leftB = ai.wallFeeler(500, heading + 115)
rightWall = ai.wallFeeler(500, heading - 90)
rightF = ai.wallFeeler(500, heading - 65)
rightB = ai.wallFeeler(500, heading - 115)
backWall = ai.wallFeeler(500, heading - 180)
backL = ai.wallFeeler(500, heading - 195)
backR = ai.wallFeeler(500, heading - 165)
trackHeadRelative = (tracking - heading)
speed = ai.selfSpeed()
def findClosestArea(x):
return {
frontWall: 1,
frontL: 2,
leftF: 3,
leftWall: 4,
leftB: 5,
backL: 6,
backWall: 7,
backR: 8,
rightB: 9,
rightWall: 10,
rightF: 11,
frontR: 12
}[x]
closestVal = min(frontWall, frontL, leftF, leftWall, leftB, backL,
backWall, backR, rightB, rightWall, rightF, frontR)
#Find the closest Wall to our ship
closestWall = findClosestArea(closestVal)
#The wall we are likely to crash into if we continue on our current course
crashWall = min(trackWall, trackL3, trackL10, trackR3, trackR10)
#Rules for turning
if closestWall == 1:
ai.setTurnSpeed(64)
ai.turnLeft(1)
turn = 0
elif closestWall == 2:
ai.setTurnSpeed(64)
ai.turnRight(1)
turn = 1
elif closestWall == 3:
ai.setTurnSpeed(52)
ai.turnRight(1)
turn = .9
elif closestWall == 4:
ai.setTurnSpeed(40)
ai.turnRight(1)
turn = .8
elif closestWall == 5:
ai.setTurnSpeed(28)
ai.turnRight(1)
turn = .7
elif closestWall == 6:
ai.setTurnSpeed(16)
ai.turnRight(1)
turn = .6
elif closestWall == 7:
pass
elif closestWall == 8:
ai.setTurnSpeed(16)
ai.turnLeft(1)
turn = .4
elif closestWall == 9:
ai.setTurnSpeed(28)
ai.turnLeft(1)
turn = .3
elif closestWall == 10:
ai.setTurnSpeed(40)
ai.turnLeft(1)
turn = .2
elif closestWall == 11:
ai.setTurnSpeed(52)
ai.turnLeft(1)
turn = .1
elif closestWall == 12:
ai.setTurnSpeed(64)
ai.turnLeft(1)
turn = 0
#Rules for thrusting
#if we are going slow and there isn't a wall in front of us
if min(frontWall, frontL, frontR) > 100 and speed < 4:
ai.thrust(1)
thrust = 1
#if we are heading toward a wall and we are not facing it
elif crashWall < 150 and (ai.angleDiff(heading, tracking) > 90):
ai.thrust(1)
thrust = 1
#If there is a wall very close behind us, get away from it
elif backWall < 20 or backL < 20 or backR < 20:
ai.thrust(1)
thrust = 1
def AI_loop(self):
# print("AI_LOOP")
if ai.selfAlive() == 0:
outputFile = open("fitness.txt", "a")
# outputFile.write(str((self.totalDists/self.counter))+"\t")
outputFile.write(str(int((self.fitness**1.2))) + "\t")
[
print(str("%.5f" % g) + "\t", end="", file=outputFile)
for g in self.chromosome
]
print("\n", end="", file=outputFile)
outputFile.close()
# Release keys
ai.thrust(0)
ai.turnLeft(0)
ai.turnRight(0)
ai.setTurnSpeed(55)
# Heuristics
frontFeelerOffset = 45
perpFeelerOffset = 90
rearFeelerOffset = 135
# turnSpeedMin = 15 # learn range: 4 - 24
turnSpeedMax = 55
speedLimit = 5 # learn range: 2-6
lowSpeedLimit = 2
targetingAccuracy = 4 # 1/2 tolerance in deg for aiming accuracy
shotIsDangerous = 130
# Acquire information
heading = int(ai.selfHeadingDeg())
tracking = int(ai.selfTrackingDeg())
###=== ENEMY FEELERS ===###
# gets angle to enemy
enemyDeg = self.angleToPointDeg(
(ai.selfX(), ai.selfY()), (ai.screenEnemyX(0), ai.screenEnemyY(0)))
enemyWallDistances = []
# maxAngleOffset = 90 # learn range: 30 - 120
# resolution = 5 # learn range: 2 - 10
distAngleTuples = []
# creates tuples of degrees and wallFeelers
for m in (0, self.maxAngleOffset, self.resolution):
distAngleTuples.append(
(enemyDeg - m, ai.wallFeeler(500, int(enemyDeg - m))))
distAngleTuples.append(
(enemyDeg + m, ai.wallFeeler(500, int(enemyDeg + m))))
# gets furthest feeler
maxFeelerAngle = max(distAngleTuples, key=self.returnSecond)
angleToOpenSpace = self.headingDiff(ai.selfHeadingDeg(),
maxFeelerAngle[0])
###=== WALL FEELERS ===###
frontWall = ai.wallFeeler(
self.genericFeelerDist,
heading) # wall feeler for wall directly ahead
leftFrontWall = ai.wallFeeler(
self.genericFeelerDist, heading +
frontFeelerOffset) # wall feeler for wall 45 degrees to the left
rightFrontWall = ai.wallFeeler(
self.genericFeelerDist, heading -
frontFeelerOffset) # wall feeler for wall 45 degrees to the right
leftWall = ai.wallFeeler(
self.genericFeelerDist, heading +
perpFeelerOffset) # wall feeler for wall 90 degrees to the left
rightWall = ai.wallFeeler(
self.genericFeelerDist, heading -
perpFeelerOffset) # wall feeler for wall 90 degrees to the right
backWall = ai.wallFeeler(self.genericFeelerDist, heading -
180) # wall feeler for wall straight back
leftBackWall = ai.wallFeeler(
self.genericFeelerDist, heading +
rearFeelerOffset) # wall feeler for wall 135 degrees to the left
rightBackWall = ai.wallFeeler(
self.genericFeelerDist, heading -
rearFeelerOffset) # wall feeler for wall 135 degrees to the right
trackWall = ai.wallFeeler(
self.genericFeelerDist,
tracking) # wall in front of where ship is moving
# Keep track of all the feeler distances
feelers = [
frontWall, leftFrontWall, rightFrontWall, leftWall, rightWall,
backWall, leftBackWall, rightBackWall, trackWall
]
# Aim assist
leftDir = (heading +
90) % 360 # angle 90 degrees to the left of current heading
rightDir = (heading - 90
) % 360 # angle 90 degrees to the right of current heading
aimer = ai.aimdir(
0
) # direction that the ship needs to turn to in order to face the enemy in degrees
shot = ai.shotAlert(
0
) # returns a danger rating of a shot, the smaller the number the more likely the shot is to hit the ship
enemyX = ai.screenEnemyX(0) # returns the closest enemy's x-coord
enemyY = ai.screenEnemyY(0) # returns the closest enemy's y-coord
selfX = ai.selfX() # returns the ship's x-coord
selfY = ai.selfY() # returns the ship's x-coord
# Fuzzy variable declaration
trackRisk = riskEval(trackWall,
ai.selfSpeed()) #risk of running into trackWall
frontRisk = riskEval(frontWall,
ai.selfSpeed()) #risk of running into frontWall
leftRisk = riskEval(leftWall,
ai.selfSpeed()) #risk of running into leftWall
rightRisk = riskEval(rightWall,
ai.selfSpeed()) #risk of running into rightWall
LFRisk = riskEval(leftFrontWall,
ai.selfSpeed()) #risk of running into leftFrontWall
RFRisk = riskEval(rightFrontWall,
ai.selfSpeed()) #risk of running into rightFrontWall
LBRisk = riskEval(leftBackWall,
ai.selfSpeed()) #risk of running into leftBackWall
RBRisk = riskEval(rightBackWall,
ai.selfSpeed()) #risk of running into rightBackWall
backRisk = riskEval(backWall,
ai.selfSpeed()) #risk of running into backWall
# Compress some wall feelers
sTrack = self.squisher(trackWall)
sLeft = self.squisher(leftFrontWall)
sRight = self.squisher(rightFrontWall)
sLeftStraight = self.squisher(leftWall)
sRightStraight = self.squisher(rightWall)
# output from neural network that tells how much to turn and which direction
turn = self.trainedNeuralNetwork(sTrack, sLeft, sRight, sLeftStraight,
sRightStraight)
###=== THRUST POWER ADJUSTMENT ===#
# Power levels
mfS = self.mfSpeed(ai.selfSpeed())
mfD = self.mfDanger(ai.shotAlert(0))
# if S is high and D is moderate or high:
p1 = max(mfS[2], min(mfD[1], mfD[2]))
# if S is moderate and D is moderate:
p2 = max(mfS[1], mfD[1])
# if S is low and D is high:
p3 = max(mfS[0], mfD[2])
# if S is moderate and D is moderate:
p4 = max(mfS[1], mfD[1])
# if S is low and D is moderate:
p5 = max(mfS[0], mfD[1])
# if S is high and D is low:
p6 = max(mfS[2], mfD[0])
# if S is moderate and D is low:
p7 = max(mfS[1], mfD[0])
# if S is low and D is low:
p8 = max(mfS[0], mfD[0])
consequents = [55, 45, 55, 36, 36, 28, 24, 30]
memberships = [p1, p2, p3, p4, p5, p6, p7, p8]
ai.setPower(self.crispify(memberships, consequents))
if ai.enemyDistance(0) > self.lastDist and ai.enemyDistance(
0) < self.enemyClose:
ai.thrust(1)
elif ai.selfSpeed(
) <= 3 and frontWall >= 200: # if speed is slow and front wall is far away, thrust
ai.thrust(1)
elif trackWall < 60 and frontWall >= 200: # if the track wall is close, thrust
ai.thrust(1)
elif backWall < 20: # if the back wall is close, thrust
ai.thrust(1)
###=== TURNING RULES ===###
# Escape shots
if shot > 0 and shot < 70:
# if a shot is closeby, turn and thrust to avoid
if self.angleDif(rightDir, ai.shotX(0)) < self.angleDif(
leftDir, ai.shotX(0)
) or self.angleDif(rightDir, ai.shotY(0)) < self.angleDif(
leftDir, ai.shotY(0)
): # if shot is coming from the right, turn away and thrust
# print("Turning: avoiding shot")#debug
ai.turnLeft(1)
ai.thrust(1)
elif self.angleDif(leftDir, ai.shotX(0)) < self.angleDif(
rightDir, ai.shotX(0)
) or self.angleDif(leftDir, ai.shotY(0)) < self.angleDif(
rightDir, ai.shotY(0)
): # if shot is coming from the left, turn away and shoot ------> change this shot is just a number
# print("Turning: avoiding shot")#debug
ai.turnRight(1)
ai.thrust(1)
# Turn towards unoccluded enemy
elif aimer >= 0 and self.angleDif(rightDir, aimer) < self.angleDif(
leftDir, aimer) and not self.enemyBehindWall(
0): # if an enemy to the right, turn and shoot it
if ai.screenEnemyX(0) >= 0:
enemyDeg = self.angleToPointDeg(
(ai.selfX(), ai.selfY()),
(ai.screenEnemyX(0), ai.screenEnemyY(0)))
ai.setTurnSpeed(
self.rangeMap(abs(enemyDeg), 0, 180, self.turnSpeedMin,
turnSpeedMax))
else:
enemyDeg = self.angleToPointDeg(
(ai.selfRadarX(), ai.selfRadarY()),
(ai.closestRadarX(), ai.closestRadarY()))
ai.setTurnSpeed(
self.rangeMap(abs(enemyDeg), 0, 180, self.turnSpeedMin,
turnSpeedMax))
# print("Turning: aiming right")#debug
ai.turnRight(1)
elif aimer >= 0 and self.angleDif(leftDir, aimer) < self.angleDif(
rightDir, aimer) and not self.enemyBehindWall(
0): # if an enemy to the left, turn and shoot it
if ai.screenEnemyX(0) >= 0:
enemyDeg = self.angleToPointDeg(
(ai.selfX(), ai.selfY()),
(ai.screenEnemyX(0), ai.screenEnemyY(0)))
ai.setTurnSpeed(
self.rangeMap(abs(enemyDeg), 0, 180, self.turnSpeedMin,
turnSpeedMax))
else:
enemyDeg = self.angleToPointDeg(
(ai.selfRadarX(), ai.selfRadarY()),
(ai.closestRadarX(), ai.closestRadarY()))
ai.setTurnSpeed(
self.rangeMap(abs(enemyDeg), 0, 180, self.turnSpeedMin,
turnSpeedMax))
# print("Turning: aiming left")#debug
ai.turnLeft(1)
#fuzzy avoid walls ahead
elif leftRisk > rightRisk and trackRisk > 0.5: # and min(feelers) < self.nearLimit: #if the left wall and track walls are close, turn right
#if enemyX >=0 and enemyY >= 0 and ai.wallBetween(selfX, selfY, enemyX, enemyY) == -1:
ai.turnRight(1)
# print("Turning: fuzzy right")#debug
elif rightRisk > leftRisk and trackRisk > 0.5: # and min(feelers) < self.nearLimit: #if the right wall and track walls are close, turn left
# if enemyX >=0 and enemyY >= 0 and ai.wallBetween(selfX, selfY, enemyX, enemyY) == -1:
ai.turnLeft(1)
# print("Turning: fuzzy left")#debug
# Turn to open space nearest the angle to the enemy
elif self.enemyBehindWall(0) and min(feelers) > self.nearLimit:
if angleToOpenSpace < 0:
# print("Turning: open space left")#debug
ai.turnLeft(1)
elif angleToOpenSpace > 0:
# print("Turning: open space right")#debug
ai.turnRight(1)
# if neural net value is not between 0.48 and 0.52 then we have to turn right or left
elif not (turn >= 0.43 and turn <= 0.57):
if turn < 0.43: # turn right if value is below 0.43
# print("Turning: neural net right")#debug
ai.turnRight(1)
elif turn > 0.57: # turn left if value is below 0.57
# print("Turning: neural net left")#debug
ai.turnLeft(1)
###=== FIRING RULES ===###
# Restrict firing to reasonably accurate attempts:
# accurate range, enemy not behind wall and enemy close enough
if self.headingDiff(
heading,
ai.aimdir(0)) < targetingAccuracy and not self.enemyBehindWall(
0) and ai.enemyDistance(0) < self.enemyFireDist:
ai.fireShot()
# print("Shot Fired")#debug
# print("Firing Dist: ", self.enemyFireDist)#debug
self.counter += 1
###=== How did we die? and other Fitness Calculations ===###
# Fitness function information
self.totalDists += ai.enemyDistance(0)
if ai.enemyDistance(0) > 0:
self.currentDist = ai.enemyDistance(0)
if self.currentDist < self.lastDist:
self.fitness += 1
self.lastDist = self.currentDist
self.fitness += 1
alive = ai.selfAlive()
message = ai.scanGameMsg(1)
# print(message)#debug
if alive == 0:
self.framesDead += 1
# print(self.framesDead, message)#debug
if self.framesDead == 2:
# print("dead now")#debug
# Ran into wall
if message.find("Beal-Morneault") != -1 and message.find(
"wall") != -1:
print("End of match: wall collision.") #debug
self.fitness -= self.wallPenalty
# Crashed into player
elif message.find("crashed.") != -1:
print("End of match: player collision.") #debug
self.fitness -= self.crashPenalty
# Killed by bullet
elif message.find("Beal-Morneault was") != -1:
print("End of match: killed by opponent.") #debug
self.fitness -= self.killedPenalty
# Killed the opponent
elif message.find("by a shot from Beal-Morneault") != -1:
print("End of match: killed the opponent!") #debug
self.fitness += self.killerBonus
else:
print("End of match: enemy died.")
self.fitness += (ai.selfScore() - ai.enemyScoreId(0)
) * self.scoreDiffBonusFactor
ai.quitAI()
else:
self.framesDead = 0
def getSendData(turn,thrust,shoot):
#make all the feelers/get current sichuation data
heading = int(ai.selfHeadingDeg())
tracking = int(ai.selfTrackingDeg())
trackHeadRelative = (tracking-heading)/360
trackWall = ai.wallFeeler(500, tracking)
trackL3 = ai.wallFeeler(500, tracking + 3)
trackL10 = ai.wallFeeler(500, tracking + 10)
trackR3 = ai.wallFeeler(500, tracking - 3)
trackR10 = ai.wallFeeler(500, tracking - 10)
frontWall = ai.wallFeeler(500, heading)
frontL = ai.wallFeeler(500, heading + 10)
frontR = ai.wallFeeler(500, heading - 10)
leftWall = ai.wallFeeler(500, heading+90)
rightWall = ai.wallFeeler(500,heading-90)
backWall = ai.wallFeeler(500, heading - 180)
backL = ai.wallFeeler(500, heading - 185)
backR = ai.wallFeeler(500, heading - 175)
speed = ai.selfSpeed()/10
#get position to enemy
enemyX = ai.screenEnemyX(0)
enemyY = ai.screenEnemyY(0)
selfX = ai.selfX()
selfY = ai.selfY()
enemyDegrees = (heading - (math.degrees(math.atan2(enemyY-selfY,enemyX-selfX))+360)%360)/360
#enemyDegrees = heading - math.degrees(math.atan2(enemyY-selfY,enemyX-selfX))-360
enemySpeed = ai.enemySpeed(0)/10
enemyMoveDirection = ai.enemyTrackingDeg(0)
distanceToEnemy = 1 - math.sqrt((selfX-enemyX)**2 + (selfY-enemyY)**2)/500
relativeTracking = (tracking-180)/360-(enemyMoveDirection-180)/360
#get shots at us
data = [heading/360,tracking/360,trackHeadRelative,speed]
for i in [trackWall,trackL3,trackL10,trackR3,trackR10,frontWall,frontL,frontR,leftWall,rightWall,backWall,backL,backR]:
if i == -1:
data.append(0)
else:
data.append(1 - i/500)
for j in [enemySpeed,enemyDegrees,relativeTracking,distanceToEnemy]:
if not math.isnan(j):
if enemyX == -1:
data.append(0)
else:
data.append(j)
else:
data.append(0)
for k in [turn,thrust,shoot]:
data.append(k)
#print("distToEnemy",data[20]*500,"relTrack",data[19]*360)
return data
def AI_loop():
#Release keys
ai.thrust(0)
ai.turnLeft(0)
ai.turnRight(0)
ai.setTurnSpeed(45)
turn, thrust, shoot = 0.5, 0, 0
maxSpeed = 3
shotAngle = 9
wallClose = 12
#Set variables"""
heading = int(ai.selfHeadingDeg())
tracking = int(ai.selfTrackingDeg())
trackWall = ai.wallFeeler(500, tracking)
trackLWall = ai.wallFeeler(500, tracking+3)
trackRWall = ai.wallFeeler(500, tracking - 3)
frontWall = ai.wallFeeler(500,heading)
flWall = ai.wallFeeler(500, heading + 10)
frWall = ai.wallFeeler(500, heading - 10)
leftWall = ai.wallFeeler(500,heading+90)
rightWall = ai.wallFeeler(500,heading-90)
trackWall = ai.wallFeeler(500,tracking)
backWall = ai.wallFeeler(500, heading - 180)
backLeftWall = ai.wallFeeler(500, heading - 185)
backRightWall = ai.wallFeeler(500, heading - 175)
speed = ai.selfSpeed()
closest = min(frontWall, leftWall, rightWall, backWall, flWall, frWall)
def closestWall(x): #Find the closest Wall
return {
frontWall : 1,
leftWall : 2,
rightWall : 3,
backWall : 4,
flWall : 5,
frWall : 6,
}[x]
wallNum = closestWall(closest)
#Code for finding the angle to the closest ship
targetX, targetY = ai.screenEnemyX(0), ai.screenEnemyY(0)
calcDir = 0
if targetX- ai.selfX() != 0:
calcDir = (math.degrees(math.atan2((targetY - ai.selfY()), (targetX- ai.selfX()))) + 360)%360
crashWall = min(trackWall, trackLWall, trackRWall) #The wall we are likely to crash into if we continue on our current course
#Rules for turning
if crashWall > wallClose*speed and closest > 25 and targetX != -1: #If we are far enough away from a predicted crash and no closer than 25 pixels to a wall we can try and aim and kill them
diff = (calcDir - heading)
if ai.shotAlert(0) > -1 and ai.shotAlert(0) < 35: #If we are about to get shot
ai.turnRight(1) #Screw aiming and turn right and thrust
ai.thrust(1)
thrust = 1
#This is arguably a horrible strategy because our sideways profile is much larger, but it's required for the grade
elif diff >= 0:
if diff >= 180:
ai.turnRight(1) #If the target is to our right- turn right
turn = 1
else :
ai.turnLeft(1) #If the target is to our left - turn left
turn = 0
else :
if diff > -180:
ai.turnRight(1) #If the target is to our right - turn right
turn = 1
else :
ai.turnLeft(1) #If the target is to our left - turn left
turn = 0
#Rules for avoiding death
else :
# if crashWall/ai.selfSpeed() > ai.closestShot() :
if wallNum == 1 or wallNum == 5 or wallNum == 6: #Front Wall is Closest (Turn Away From It)
ai.turnLeft(1)
turn = 0
elif wallNum == 2 : # Left Wall is Closest (Turn Away From It)
ai.turnRight(1)
turn = 1
elif wallNum == 3 : #Right Wall is Closest (Turn Away From It)
ai.turnLeft(1)
turn = 0
else : #Back Wall is closest- turn so that we are facing directly away from it
if backLeftWall < backRightWall:
ai.turnRight(1) #We need to turn right to face more directly away from it
turn = 1
if backLeftWall > backRightWall: # We need to turn left to face more directly away from it
ai.turnLeft(1)
turn = 0
#Rules for thrusting
if speed < maxSpeed and frontWall > 100: #If we are moving slowly and we won't ram into anything, accelerate
ai.thrust(1)
thrust = 1
elif trackWall < 250 and (ai.angleDiff(heading, tracking) > 120): #If we are getting close to a wall, and we can thrust away from it, do so
ai.thrust(1)
thrust = 1
elif backWall < 20: #If there is a wall very close behind us, get away from it
ai.thrust(1)
thrust = 1
if abs(calcDir - heading) < shotAngle : #If we are close to the current proper trajectory for a shot then fire
ai.fireShot()
shoot = 1
#adjust the the learning NN
infile = open("myBotWeights.txt","r")
weight = eval(infile.read())
infile.close()
sendData = getSendData(turn, thrust, shoot)
weight = adjustNN(sendData, 21, 8, 3, weight)
outfile = open("myBotWeights.txt","w")
outfile.write(str(weight))
outfile.close()
def AI_loop(self):
# Release keys
ai.thrust(0)
ai.turnLeft(0)
ai.turnRight(0)
# ai.setPower(30)
#-------------------- Set variables --------------------#
heading = int(ai.selfHeadingDeg())
tracking = int(ai.selfTrackingDeg())
frontWall = ai.wallFeeler(500, heading)
leftWall = ai.wallFeeler(500, heading + 45)
rightWall = ai.wallFeeler(500, heading - 45)
leftWallStraight = ai.wallFeeler(500, heading + 90)
rightWallStraight = ai.wallFeeler(500, heading - 90)
leftBack = ai.wallFeeler(500, heading + 135)
rightBack = ai.wallFeeler(500, heading - 135)
backWall = ai.wallFeeler(500, heading - 180)
trackWall = ai.wallFeeler(500, tracking)
R = (heading - 90) % 360
L = (heading + 90) % 360
aim = ai.aimdir(0)
bullet = ai.shotAlert(0)
speed = ai.selfSpeed()
x = ai.selfX()
y = ai.selfY()
targetX = self.coordinateList[self.counter % self.coordListLength][0]
targetY = self.coordinateList[self.counter % self.coordListLength][1]
toTurn = self.angleToPoint(x, y, targetX, targetY, heading)
distance = self.distance(x, targetX, y, targetY)
#-------------------- Print statements --------------------#
print("(x, y): (", x, ",", y, ")")
print("destination: ",
self.coordinateList[self.counter % self.coordListLength])
print("distance: ", distance)
# print("closestEnemyX: ", closestEnemyX)
# print("closestEnemyY: ", closestEnemyY)
# print("difference x: ", differenceX)
# print("difference y: ", differenceY)
# print("degrees: ", degrees)
# print("screen enemy? ", ai.screenEnemyXId(ai.closestShipId()))
print("toTurn: ", toTurn)
print()
#-------------------- Move to target point --------------------#
# if toTurn > 0 and toTurn < 30 and distance > 300 and speed <= 15 and speed >= 4:
if abs(toTurn) < 20 and distance > 200:
print("Lock!")
ai.turnLeft(0)
ai.turnRight(0)
if self.frames % 40 == 0:
ai.thrust(1)
elif toTurn >= 20:
print("Turning right!")
ai.turnLeft(1)
elif toTurn <= -20:
ai.turnRight(1)
print("Turning left!")
if distance < 200:
# ai.thrust(0)
self.counter = self.counter + 1
# #-------------------- Thrust rules --------------------#
# if speed <= 3 and frontWall >= 200:
# print("Front wall far")
# ai.thrust(1)
# elif trackWall < 50:
# print("Close to track wall")
# ai.thrust(1)
# elif backWall < 40:
# print("Close to back wall")
# ai.thrust(1)
# #---------------- Turn rules ----------------#
# # Figures out what corner we are in and turns the right directon
# if (backWall < 30) and (rightWallStraight < 200):
# print("Corners 1")
# ai.turnLeft(1)
# elif backWall < 30 and (leftWallStraight < 200):
# print("Corners 2")
# ai.turnRight(1)
# # Walls along our periphery (90 degree feelers)
# elif leftWallStraight < rightWallStraight and trackWall < 75:
# print("90 left danger")
# ai.turnRight(1)
# elif leftWallStraight > rightWallStraight and trackWall < 75:
# print("90 right danger")
# ai.turnLeft(1)
self.frames = self.frames + 1