def pacmanSuccessorStateAxioms(x, y, t, walls_grid):
"""
Successor state axiom for state (x,y,t) (from t-1), given the board (as a
grid representing the wall locations).
Current <==> (previous position at time t-1) & (took action to move to x, y)
"""
"*** YOUR CODE HERE ***"
successor_list = []
if 0 <= x - 1 < walls_grid.width and 0 <= y < walls_grid.height:
if not walls_grid.data[x - 1][y]:
location = logic.PropSymbolExpr('P', x - 1, y, t - 1)
action = logic.PropSymbolExpr('East', t - 1)
successor_list.append(location & action)
if 0 <= x + 1 < walls_grid.width and 0 <= y < walls_grid.height:
if not walls_grid.data[x + 1][y]:
location = logic.PropSymbolExpr('P', x + 1, y, t - 1)
action = logic.PropSymbolExpr('West', t - 1)
successor_list.append(location & action)
if 0 <= x < walls_grid.width and 0 <= y - 1 < walls_grid.height:
if not walls_grid.data[x][y - 1]:
location = logic.PropSymbolExpr('P', x, y - 1, t - 1)
action = logic.PropSymbolExpr('North', t - 1)
successor_list.append(location & action)
if 0 <= x < walls_grid.width and 0 <= y + 1 < walls_grid.height:
if not walls_grid.data[x][y + 1]:
location = logic.PropSymbolExpr('P', x, y + 1, t - 1)
action = logic.PropSymbolExpr('South', t - 1)
successor_list.append(location & action)
return logic.PropSymbolExpr('P', x, y, t) % logic.associate(
'|', successor_list)
def atMostOne(expressions) :
"""
Given a list of logic.Expr instances, return a single logic.Expr instance in CNF (conjunctive normal form)
that represents the logic that at most one of the expressions in the list is true.
"""
"*** YOUR CODE HERE ***"
exprCNF = ~(atLeastOne(expressions))
i = 0
while i < len(expressions):
j = 0
exprAtMostOne = []
while j < len(expressions):
if expressions[j] == expressions[i]:
exprAtMostOne.append(expressions[j])
else:
exprAtMostOne.append(~expressions[j])
j = j + 1
exprCNF = exprCNF | logic.associate('&', exprAtMostOne)
i = i + 1
#print exprCNF
return exprCNF
def generate_initial_statements(problem):
temp_list = []
initial_position_expr = logic.PropSymbolExpr("P", start[0], start[1], time)
for x in range(0, problem.getWidth()):
for y in range(0, problem.getHeight()):
if (x,y) == (start[0], start[1]):
continue
else:
temp_list.append(logic.PropSymbolExpr("P", x, y, time))
initial_position_expr = initial_position_expr & ~(logic.associate('|', temp_list))
return initial_position_expr
def result(self, state, action):
terms = parse_state(state)
sentence = str(
logic.associate(
'&',
action(logic.conjuncts(state), action.args).clauses))
#print('------------\nBefore: ' + sentence)
while sentence.find('divide(x)') != -1:
quotient = terms[4] / terms[0]
terms[0] = 1
terms[4] = quotient
sentence = sentence.replace('divide(x)', '{:.2f}'.format(quotient))
while sentence.find('combine') != -1:
start = sentence.find('combine')
term = int(sentence[start + 9]) - 1
if term < 3:
new_val = terms[term] + terms[2]
terms[term] = new_val
terms[2] = 0
else:
new_val = terms[term] + terms[5]
terms[term] = new_val
terms[5] = 0
sentence = sentence.replace(sentence[start:(start + 11)],
str(new_val))
while sentence.find('inverse') != -1:
start = sentence.find('inverse')
term = int(sentence[start + 9]) - 1
new_val = -1 * terms[term]
if term == 3:
terms[2] = new_val
elif term == 1:
terms[5] = new_val
terms[term] = 0
sentence = sentence.replace(sentence[start:(start + 11)],
str(new_val))
#print('After: ' + sentence + '\n------------')
return logic.associate('&', self.convert(sentence.replace('Not', '~')))
def atLeastOne(expressions) :
"""
Given a list of logic.Expr instances, return a single logic.Expr instance in CNF (conjunctive normal form)
that represents the logic that at least one of the expressions in the list is true.
>>> A = logic.PropSymbolExpr('A');
>>> B = logic.PropSymbolExpr('B');
>>> symbols = [A, B]
>>> atleast1 = atLeastOne(symbols)
>>> model1 = {A:False, B:False}
>>> print logic.pl_true(atleast1,model1)
False
>>> model2 = {A:False, B:True}
>>> print logic.pl_true(atleast1,model2)
True
>>> model3 = {A:True, B:True}
>>> print logic.pl_true(atleast1,model2)
True
"""
"*** YOUR CODE HERE ***"
return logic.associate('|', expressions)
def positionLogicPlan(problem):
"""
Given an instance of a PositionSearchProblem, return a list of actions that lead to the goal.
Available actions are game.Directions.{NORTH,SOUTH,EAST,WEST}
Note that STOP is not an available action.
destination_time1 <=> (src1_time0 & action1_time0) | src2_time0 & action2_0) |(src3_time0 & action3_time0)
and your goal state can just be like:
goal_timeT
then you plug it in for each value of time (0-50)
"""
"*** YOUR CODE HERE ***"
cnf = []
maxTime = 51
n = Directions.NORTH
s = Directions.SOUTH
e = Directions.EAST
w = Directions.WEST
DirectionsList = [n, s, e , w]
width = problem.getWidth()+1
height = problem.getHeight()+1
for time in range(0, maxTime):
stateLogicList = []
if time == 0: #Only need Start/Goal
# Start State
startState = problem.getStartState()
pacmanStart = logic.PropSymbolExpr("P", startState[0], startState[1], 0)
nonStartStates = []
for x in range(1, width):
for y in range(1, height):
if (x,y) == (startState[0], startState[1]):
continue
else
nonStartStates.append(logic.PropSymbolExpr("P", x, y, 0))
startLogic = logic.to_cnf(pacmanStart & ~(logic.associate('|', nonStartStates)))
cnf.append(startLogic)
else:
for x in range(1,width):
for y in range(1, height):
currentState = (x,y)
currentLogic = logic.PropSymbolExpr("P", currentState[0], currentState[1], time)
for action in problem.actions(currentState):
if action == n:
nextstate = problem.result(currentState, action)[0]
logic.PropSymbolExpr("P", x, y+1, time-1)
nextaction = logic.PropSymbolExpr(s, time-1)
elif action == s:
nextstate = logic.PropSymbolExpr("P", x, y-1, time-1)
nextaction = logic.PropSymbolExpr(n, time-1)
elif action == e:
nextstate = logic.PropSymbolExpr("P", x+1, y, time-1)
nextaction = logic.PropSymbolExpr(w, time-1)
elif action == w:
nextstate = logic.PropSymbolExpr("P", x-1, y, time-1)
nextaction = logic.PropSymbolExpr(e, time-1)
stateLogicList.append((currentLogic, (nextstate & nextaction)))
dictionary = {}
for elem in stateLogicList:
if elem[0] not in dictionary.keys():
dictionary[elem[0]] = [elem[1]]
if elem[0] in dictionary.keys():
dictionary[elem[0]].append(elem[1])
for key in dictionary.keys():
val = dictionary[key]
parents = logic.associate('|', val)
cnf.append(logic.to_cnf(key % parents))
# exactly one action is taken at one time
Dir = []
for direction in DirectionsList:
Dir.append(logic.PropSymbolExpr(direction, time))
OneMove = exactlyOne(Dir)
cnf.append(logic.to_cnf(OneMove))
#Goal State
goalState = problem.getGoalState()
cnf.append(logic.to_cnf(logic.PropSymbolExpr("P", goalState[0], goalState[1], time)))
model = logic.pycoSAT(cnf)
if model:
return extractActionSequence(model, DirectionsList)
#remove goal if the model is false
cnf.remove(logic.PropSymbolExpr("P", goalState[0], goalState[1], time))
def get_next_action(self, observation):
# get observation for the current state and return next action to apply (and None if no action is applicable)
#observation is a dictionary with spaceship_name:number_of_laser_around it.
global my_world
print("my_world_is:")
print(my_world)
print("this is the observation:")
print(observation)
spaceships = my_world[0]
devices = my_world[1]
all_targets = my_world[2]
#update spaceships and devices if there is spaceship that exploded
for device in devices:
if device[0] in observation:
ship_name = device[0]
if observation[ship_name] == -1: #ship exploded
temp_list = list(devices)
temp_list.remove(device)
devices = tuple(temp_list)
for ship in spaceships:
if ship[0] in observation:
ship_name = ship[0]
if observation[ship_name] == -1: # ship exploded
temp_list = list(spaceships)
temp_list.remove(ship)
spaceships = tuple(temp_list)
#updated world after removing ships that exploded. important for the GBFS running in the next lines
my_world = (spaceships, devices, all_targets)
#all ships exploded
if not devices or not spaceships:
return None
##########################
#running GBFS from current world
p = SpaceshipProblem(my_world)
timeout = 60
result = check_problem(
p, (lambda p: search.best_first_graph_search(p, p.h)), timeout)
print("GBFS ", result)
##########################
#updating the world representation
next_action = result[2][0]
if next_action[0] in ("turn_on", "use", "calibrate"):
self.update_my_world(next_action)
return next_action
#for all locations without lasers, make a tuple of their neighbors and mark them as safe - without lasers.
all_neighbors = ()
all_neighbors = (next_action[2], ) + all_neighbors
for sname, nb_lasers in observation.items():
if nb_lasers == 0:
for shipname, location in spaceships:
if shipname == sname:
ship_all_neighbors = self.get_neighbors(location)
for i in ship_all_neighbors:
if i not in all_neighbors:
all_neighbors = (i, ) + all_neighbors
for i in all_neighbors:
self.lasers_logic.tell(~(self.grid_dict[i]))
#if the action is move for some ship and there isn't lasers around it, go ahead and do it.
for sname, nb_lasers in observation.items():
if next_action[1] == sname and nb_lasers == 0 and next_action[
0] == "move":
self.update_my_world(next_action)
return next_action
#if the code is here, then the gbfs wants to move a ship with lasers around it
#next_action[0] = "move", next_action[1] = ship name, next_action[2] = from, next_action[3] = to
n_combinations = []
for ship_name, ship_location in spaceships:
if ship_name == next_action[1]:
near_by_n = self.get_neighbors(ship_location)
near_by_n = (ship_location, ) + near_by_n
nb_lasers = observation[ship_name]
n_combinations = (itertools.combinations(
list(near_by_n),
len(near_by_n) - nb_lasers))
combination_list = list(n_combinations)
small_combinations = (combination_list[0], combination_list[1],
combination_list[2])
logic_list = []
for combination in small_combinations:
temp = []
for coord in combination:
temp.append(~self.grid_dict[coord])
logic_list.append(logic.associate('&', temp))
self.lasers_logic.tell(logic.associate('|', logic_list))
logic_answer = logic.dpll_satisfiable(
logic.to_cnf(logic.associate('&', self.lasers_logic.clauses)))
#logic answer contains a dict of Lxyz = Flase/True. when False means that the (x,y,z) location is safe, and unsafe
#(contains lasers) otherwise
#if "to_location" of GBFS is in logic_answer and is false - use it,
#else we would like to choose a random one that is not our current location
print("logic answer:", logic_answer)
# gbfs_to_location = self.grid_dict[next_action[3]]
# logic_answer.delete(self.grid_dict[next_action[2]])
for k, v in logic_answer.items():
if v == True:
logic_answer = self.minus_key(k, logic_answer)
#remove from logic answer not neighbors
nears = ()
neighbors = self.get_neighbors(next_action[2])
for n in neighbors:
temp = self.grid_dict[n]
nears = (temp, ) + nears
for l in logic_answer:
if l not in nears:
logic_answer = self.minus_key(l, logic_answer)
#remove targets locations
for t in all_targets:
temp = self.grid_dict[t]
if temp in logic_answer:
logic_answer = self.minus_key(temp, logic_answer)
#remove spaceships locations
for ship_name, location in spaceships:
temp = self.grid_dict[location]
if temp in logic_answer:
logic_answer = self.minus_key(temp, logic_answer)
print("whats left for random: ", list(logic_answer.keys()))
random_to_location = random.choice(list(logic_answer.keys()))
print("random choise:", random_to_location)
if not random_to_location: #empty
return None
#return Lxyz form to (x,y,z)
new_to_location = ()
for k, v in self.grid_dict.items():
if v == random_to_location:
new_to_location = k
print("new_to_location:", new_to_location)
new_next_action = ("move", next_action[1], next_action[2],
new_to_location)
print("new next location", new_next_action)
self.update_my_world(new_next_action)
return new_next_action
import logic
if __name__ == '__main__':
wumpus_kb = logic.PropKB()
P11, P12, P21, P22, P31, B11, B21 = logic.expr(
'P11, P12, P21, P22, P31, B11, B21')
#B100 = logic.expr('B100')
wumpus_kb.tell(~P11)
wumpus_kb.tell(B11 | '<=>' | ((P12 | P21)))
wumpus_kb.tell(B21 | '<=>' | ((P11 | P22 | P31)))
wumpus_kb.tell(~B11)
ship = (1, 23, 4)
shipstr = 'P' + str((ship[0] + 1, ship[1], ship[2]))
#for v in ship:
# shipstr += str(v)
print(shipstr)
wumpus_kb.tell(~logic.expr(shipstr))
result = logic.dpll_satisfiable(
logic.to_cnf(
logic.associate('&', wumpus_kb.clauses + [logic.expr(P22)])))
print(result)
result = logic.dpll_satisfiable(
logic.to_cnf(
logic.associate('&', wumpus_kb.clauses + [logic.expr(shipstr)])))
print(result)
def foodLogicPlan(problem):
"""
Given an instance of a FoodSearchProblem, return a list of actions that help Pacman
eat all of the food.
Available actions are game.Directions.{NORTH,SOUTH,EAST,WEST}
Note that STOP is not an available action.
"""
"*** YOUR CODE HERE ***"
cnf = []
maxTime = 51
n = Directions.NORTH
s = Directions.SOUTH
e = Directions.EAST
w = Directions.WEST
DirectionsList = [n, s, e , w]
width = problem.getWidth()+1
height = problem.getHeight()+1
#Starting State
swag = problem.getStartState()
startState = swag[0]
#Get positions of food
foodGrid = swag[1]
foodPosList = []
for x in range(width+1):
for y in range(height+1):
if foodGrid[x][y]:
foodPosList.append((x,y))
pacmanStart = logic.PropSymbolExpr("P", startState[0], startState[1], 0)
nonStartStates = []
for x in range(1, width):
for y in range(1, height):
if (x,y) == (startState[0], startState[1]):
continue
else:
nonStartStates.append(logic.PropSymbolExpr("P", x, y, 0))
startLogic = logic.to_cnf(pacmanStart & ~(logic.associate('|', nonStartStates)))
cnf.append(startLogic)
stateList = []
for x in range(width+1):
for y in range(height+1):
if problem.isWall((x,y)):
continue
else:
stateList.append((x,y))
for time in range(maxTime):
#print time
oneStateList = []
for state in stateList:
oneStateList.append(logic.PropSymbolExpr("P",state[0],state[1], time))
legalActionList = problem.actions((state, foodGrid))
illegalList = []
for action in DirectionsList:
if action in legalActionList:
nextState = problem.result((state, foodGrid), action)[0][0]
# state & action >> new state
nextLogic = (logic.PropSymbolExpr("P",state[0],state[1], time) & logic.PropSymbolExpr(action,time)) >> logic.PropSymbolExpr('P',nextState[0],nextState[1], time+1)
cnf.append(logic.to_cnf(nextLogic))
else:
illegalList.append(action)
for action in illegalList:
# state >> not illegal action
cnf.append(logic.to_cnf(logic.PropSymbolExpr("P",state[0],state[1], time) >> ~logic.PropSymbolExpr(action,time)))
# uses oneStateList, makes sure we are not in two places at once
oneState = exactlyOne(oneStateList)
cnf.append((oneState))
# Exactly 1 move per turn
Dir = []
for direction in DirectionsList:
Dir.append(logic.PropSymbolExpr(direction, time))
oneMove = exactlyOne(Dir)
cnf.append(logic.to_cnf(oneMove))
# goal state (must hit each pellet once)
foodAllEaten = []
for food in foodPosList:
foodOnce = []
for alltime in range(time+1):
foodOnce.append(logic.PropSymbolExpr('P',food[0],food[1],alltime))
atLeastOnce = logic.associate('|', foodOnce)
foodAllEaten.append(atLeastOnce)
goalLogic = logic.associate('&', foodAllEaten)
cnf.append(goalLogic)
model = logic.pycoSAT(cnf)
if model:
path = extractActionSequence(model, DirectionsList)
return path
cnf.remove(goalLogic)
print("you suck")
def foodGhostLogicPlan(problem):
"""
Given an instance of a FoodGhostSearchProblem, return a list of actions that help Pacman
eat all of the food and avoid patrolling ghosts.
Ghosts only move east and west. They always start by moving East, unless they start next to
and eastern wall.
Available actions are game.Directions.{NORTH,SOUTH,EAST,WEST}
Note that STOP is not an available action.
"""
"*** YOUR CODE HERE ***"
cnf = []
maxTime = 51
n = Directions.NORTH
s = Directions.SOUTH
e = Directions.EAST
w = Directions.WEST
DirectionsList = [n, s, e , w]
width = problem.getWidth()+1
height = problem.getHeight()+1
#Starting State
swag = problem.getStartState()
startState = swag[0]
ghostStartStateList = problem.getGhostStartStates()
#Get positions of food
foodGrid = swag[1]
foodPosList = []
for x in range(width+1):
for y in range(height+1):
if foodGrid[x][y]:
foodPosList.append((x,y))
pacmanStart = logic.PropSymbolExpr("P", startState[0], startState[1], 0)
nonStartStates = []
for x in range(1, width):
for y in range(1, height):
if (x,y) == (startState[0], startState[1]):
continue
else:
nonStartStates.append(logic.PropSymbolExpr("P", x, y, 0))
startLogic = logic.to_cnf(pacmanStart & ~(logic.associate('|', nonStartStates)))
cnf.append(startLogic)
stateList = []
for x in range(width+1):
for y in range(height+1):
if problem.isWall((x,y)):
continue
else:
stateList.append((x,y))
for time in range(maxTime):
oneStateList = []
for state in stateList:
oneStateList.append(logic.PropSymbolExpr("P",state[0],state[1], time))
legalActionList = problem.actions((state, foodGrid))
illegalList = []
for action in DirectionsList:
if action in legalActionList:
nextState = problem.result((state, foodGrid), action)[0][0]
# state & action >> new state
nextLogic = (logic.PropSymbolExpr("P",state[0],state[1], time) & logic.PropSymbolExpr(action,time)) >> logic.PropSymbolExpr('P',nextState[0],nextState[1], time+1)
cnf.append(logic.to_cnf(nextLogic))
else:
illegalList.append(action)
for action in illegalList:
# state >> not illegal action
cnf.append(logic.to_cnf(logic.PropSymbolExpr("P",state[0],state[1], time) >> ~logic.PropSymbolExpr(action,time)))
# uses oneStateList, makes sure we are not in two places at once
oneState = exactlyOne(oneStateList)
cnf.append((oneState))
# Exactly 1 move per turn
Dir = []
for direction in DirectionsList:
Dir.append(logic.PropSymbolExpr(direction, time))
oneMove = exactlyOne(Dir)
cnf.append(logic.to_cnf(oneMove))
# goal state (must hit each pellet once)
foodAllEaten = []
for food in foodPosList:
foodOnce = []
for alltime in range(time+1):
foodOnce.append(logic.PropSymbolExpr('P',food[0],food[1],alltime))
atLeastOnce = logic.associate('|', foodOnce)
foodAllEaten.append(atLeastOnce)
goalLogic = logic.associate('&', foodAllEaten)
cnf.append(goalLogic)
#Pacman and Ghost not in same place
def ghostPositionfinder(ghoststart, time):
ghostposition = ghoststart
x = ghoststart[0]
y = ghoststart[1]
East = True
for t in range(time):
if East == True:
x += 1
if problem.isWall((x,y)):
x -= 2
East = False
elif East == False:
x -= 1
if problem.isWall((x,y)):
x += 2
East = True
return (x,y)
#logic.PropSymbolExpr("G", ghostPos[0], ghostPos[1], 0)
for ghostStartState in ghostStartStateList:
ghostPos = ghostStartState.getPosition()
ghostCurrentPos = ghostPositionfinder(ghostPos, time)
cnf.append(logic.PropSymbolExpr("G", ghostCurrentPos[0], ghostCurrentPos[1], time))
for pos in stateList:
plsnodie = [logic.PropSymbolExpr("P",pos[0],pos[1],time)] + [logic.PropSymbolExpr("G",pos[0],pos[1],time)]
cnf.append(atMostOne(plsnodie))
plsnodie = [logic.PropSymbolExpr("P",pos[0],pos[1],time)] + [logic.PropSymbolExpr("G",pos[0],pos[1],time-1)]
cnf.append(atMostOne(plsnodie))
model = logic.pycoSAT(cnf)
if model:
path = extractActionSequence(model, DirectionsList)
return path
cnf.remove(goalLogic)
print("you suck")
def positionLogicPlan(problem):
"""
Given an instance of a PositionSearchProblem, return a list of actions that lead to the goal.
Available actions are game.Directions.{NORTH,SOUTH,EAST,WEST}
Note that STOP is not an available action.
"""
"*** YOUR CODE HERE ***"
cnf = []
maxTime = 51
n = Directions.NORTH
s = Directions.SOUTH
e = Directions.EAST
w = Directions.WEST
DirectionsList = [n, s, e , w]
width = problem.getWidth()+1
height = problem.getHeight()+1
#Starting State
startState = problem.getStartState()
pacmanStart = logic.PropSymbolExpr("P", startState[0], startState[1], 0)
nonStartStates = []
for x in range(1, width):
for y in range(1, height):
if (x,y) == (startState[0], startState[1]):
continue
else:
nonStartStates.append(logic.PropSymbolExpr("P", x, y, 0))
startLogic = logic.to_cnf(pacmanStart & ~(logic.associate('|', nonStartStates)))
cnf.append(startLogic)
goalState = problem.getGoalState()
stateList = []
for x in range(width+1):
for y in range(height+1):
if problem.isWall((x,y)):
continue
else:
stateList.append((x,y))
for time in range(maxTime):
oneStateList = []
for state in stateList:
oneStateList.append(logic.PropSymbolExpr("P",state[0],state[1], time))
legalActionList = problem.actions(state)
illegalList = []
for action in DirectionsList:
if action in legalActionList:
nextState = problem.result(state, action)[0]
# state & action >> new state
nextLogic = (logic.PropSymbolExpr("P",state[0],state[1], time) & logic.PropSymbolExpr(action,time)) >> logic.PropSymbolExpr('P',nextState[0],nextState[1], time+1)
cnf.append(logic.to_cnf(nextLogic))
else:
illegalList.append(action)
for action in illegalList:
# state >> not illegal action
cnf.append(logic.to_cnf(logic.PropSymbolExpr('P',state[0],state[1], time) >> ~logic.PropSymbolExpr(action,time)))
# uses oneStateList, makes sure we are not in two places at once
oneState = exactlyOne(oneStateList)
cnf.append((oneState))
# Exactly 1 move per turn
Dir = []
for direction in DirectionsList:
Dir.append(logic.PropSymbolExpr(direction, time))
oneMove = exactlyOne(Dir)
cnf.append(logic.to_cnf(oneMove))
# goal state
cnf.append(logic.PropSymbolExpr("P",goalState[0],goalState[1], time))
#print time
model = logic.pycoSAT(cnf)
if model:
path = extractActionSequence(model, DirectionsList)
return path
cnf.remove(logic.PropSymbolExpr("P",goalState[0],goalState[1], time))
def foodGhostLogicPlan(problem):
"""
Given an instance of a FoodGhostSearchProblem, return a list of actions that help Pacman
eat all of the food and avoid patrolling ghosts.
Ghosts only move east and west. They always start by moving East, unless they start next to
and eastern wall.
Available actions are game.Directions.{NORTH,SOUTH,EAST,WEST}
Note that STOP is not an available action.
"""
"*** YOUR CODE HERE ***"
cnf = []
maxTime = 51
n = Directions.NORTH
s = Directions.SOUTH
e = Directions.EAST
w = Directions.WEST
DirectionsList = [n, s, e, w]
width = problem.getWidth() + 1
height = problem.getHeight() + 1
#Starting State
swag = problem.getStartState()
startState = swag[0]
ghostStartStateList = problem.getGhostStartStates()
#Get positions of food
foodGrid = swag[1]
foodPosList = []
for x in range(width + 1):
for y in range(height + 1):
if foodGrid[x][y]:
foodPosList.append((x, y))
pacmanStart = logic.PropSymbolExpr("P", startState[0], startState[1], 0)
nonStartStates = []
for x in range(1, width):
for y in range(1, height):
if (x, y) == (startState[0], startState[1]):
continue
else:
nonStartStates.append(logic.PropSymbolExpr("P", x, y, 0))
startLogic = logic.to_cnf(
pacmanStart & ~(logic.associate('|', nonStartStates)))
cnf.append(startLogic)
stateList = []
for x in range(width + 1):
for y in range(height + 1):
if problem.isWall((x, y)):
continue
else:
stateList.append((x, y))
for time in range(maxTime):
oneStateList = []
for state in stateList:
oneStateList.append(
logic.PropSymbolExpr("P", state[0], state[1], time))
legalActionList = problem.actions((state, foodGrid))
illegalList = []
for action in DirectionsList:
if action in legalActionList:
nextState = problem.result((state, foodGrid), action)[0][0]
# state & action >> new state
nextLogic = (logic.PropSymbolExpr(
"P", state[0], state[1], time) & logic.PropSymbolExpr(
action, time)) >> logic.PropSymbolExpr(
'P', nextState[0], nextState[1], time + 1)
cnf.append(logic.to_cnf(nextLogic))
else:
illegalList.append(action)
for action in illegalList:
# state >> not illegal action
cnf.append(
logic.to_cnf(
logic.PropSymbolExpr("P", state[0], state[1], time) >>
~logic.PropSymbolExpr(action, time)))
# uses oneStateList, makes sure we are not in two places at once
oneState = exactlyOne(oneStateList)
cnf.append((oneState))
# Exactly 1 move per turn
Dir = []
for direction in DirectionsList:
Dir.append(logic.PropSymbolExpr(direction, time))
oneMove = exactlyOne(Dir)
cnf.append(logic.to_cnf(oneMove))
# goal state (must hit each pellet once)
foodAllEaten = []
for food in foodPosList:
foodOnce = []
for alltime in range(time + 1):
foodOnce.append(
logic.PropSymbolExpr('P', food[0], food[1], alltime))
atLeastOnce = logic.associate('|', foodOnce)
foodAllEaten.append(atLeastOnce)
goalLogic = logic.associate('&', foodAllEaten)
cnf.append(goalLogic)
#Pacman and Ghost not in same place
def ghostPositionfinder(ghoststart, time):
ghostposition = ghoststart
x = ghoststart[0]
y = ghoststart[1]
East = True
for t in range(time):
if East == True:
x += 1
if problem.isWall((x, y)):
x -= 2
East = False
elif East == False:
x -= 1
if problem.isWall((x, y)):
x += 2
East = True
return (x, y)
#logic.PropSymbolExpr("G", ghostPos[0], ghostPos[1], 0)
for ghostStartState in ghostStartStateList:
ghostPos = ghostStartState.getPosition()
ghostCurrentPos = ghostPositionfinder(ghostPos, time)
cnf.append(
logic.PropSymbolExpr("G", ghostCurrentPos[0],
ghostCurrentPos[1], time))
for pos in stateList:
plsnodie = [logic.PropSymbolExpr("P", pos[0], pos[1], time)
] + [logic.PropSymbolExpr("G", pos[0], pos[1], time)]
cnf.append(atMostOne(plsnodie))
plsnodie = [logic.PropSymbolExpr("P", pos[0], pos[1], time)] + [
logic.PropSymbolExpr("G", pos[0], pos[1], time - 1)
]
cnf.append(atMostOne(plsnodie))
model = logic.pycoSAT(cnf)
if model:
path = extractActionSequence(model, DirectionsList)
return path
cnf.remove(goalLogic)
print("you suck")
def foodLogicPlan(problem):
"""
Given an instance of a FoodSearchProblem, return a list of actions that help Pacman
eat all of the food.
Available actions are game.Directions.{NORTH,SOUTH,EAST,WEST}
Note that STOP is not an available action.
"""
"*** YOUR CODE HERE ***"
cnf = []
maxTime = 51
n = Directions.NORTH
s = Directions.SOUTH
e = Directions.EAST
w = Directions.WEST
DirectionsList = [n, s, e, w]
width = problem.getWidth() + 1
height = problem.getHeight() + 1
#Starting State
swag = problem.getStartState()
startState = swag[0]
#Get positions of food
foodGrid = swag[1]
foodPosList = []
for x in range(width + 1):
for y in range(height + 1):
if foodGrid[x][y]:
foodPosList.append((x, y))
pacmanStart = logic.PropSymbolExpr("P", startState[0], startState[1], 0)
nonStartStates = []
for x in range(1, width):
for y in range(1, height):
if (x, y) == (startState[0], startState[1]):
continue
else:
nonStartStates.append(logic.PropSymbolExpr("P", x, y, 0))
startLogic = logic.to_cnf(
pacmanStart & ~(logic.associate('|', nonStartStates)))
cnf.append(startLogic)
stateList = []
for x in range(width + 1):
for y in range(height + 1):
if problem.isWall((x, y)):
continue
else:
stateList.append((x, y))
for time in range(maxTime):
#print time
oneStateList = []
for state in stateList:
oneStateList.append(
logic.PropSymbolExpr("P", state[0], state[1], time))
legalActionList = problem.actions((state, foodGrid))
illegalList = []
for action in DirectionsList:
if action in legalActionList:
nextState = problem.result((state, foodGrid), action)[0][0]
# state & action >> new state
nextLogic = (logic.PropSymbolExpr(
"P", state[0], state[1], time) & logic.PropSymbolExpr(
action, time)) >> logic.PropSymbolExpr(
'P', nextState[0], nextState[1], time + 1)
cnf.append(logic.to_cnf(nextLogic))
else:
illegalList.append(action)
for action in illegalList:
# state >> not illegal action
cnf.append(
logic.to_cnf(
logic.PropSymbolExpr("P", state[0], state[1], time) >>
~logic.PropSymbolExpr(action, time)))
# uses oneStateList, makes sure we are not in two places at once
oneState = exactlyOne(oneStateList)
cnf.append((oneState))
# Exactly 1 move per turn
Dir = []
for direction in DirectionsList:
Dir.append(logic.PropSymbolExpr(direction, time))
oneMove = exactlyOne(Dir)
cnf.append(logic.to_cnf(oneMove))
# goal state (must hit each pellet once)
foodAllEaten = []
for food in foodPosList:
foodOnce = []
for alltime in range(time + 1):
foodOnce.append(
logic.PropSymbolExpr('P', food[0], food[1], alltime))
atLeastOnce = logic.associate('|', foodOnce)
foodAllEaten.append(atLeastOnce)
goalLogic = logic.associate('&', foodAllEaten)
cnf.append(goalLogic)
model = logic.pycoSAT(cnf)
if model:
path = extractActionSequence(model, DirectionsList)
return path
cnf.remove(goalLogic)
print("you suck")
def positionLogicPlan(problem):
"""
Given an instance of a PositionSearchProblem, return a list of actions that lead to the goal.
Available actions are game.Directions.{NORTH,SOUTH,EAST,WEST}
Note that STOP is not an available action.
"""
"*** YOUR CODE HERE ***"
cnf = []
maxTime = 51
n = Directions.NORTH
s = Directions.SOUTH
e = Directions.EAST
w = Directions.WEST
DirectionsList = [n, s, e, w]
width = problem.getWidth() + 1
height = problem.getHeight() + 1
#Starting State
startState = problem.getStartState()
pacmanStart = logic.PropSymbolExpr("P", startState[0], startState[1], 0)
nonStartStates = []
for x in range(1, width):
for y in range(1, height):
if (x, y) == (startState[0], startState[1]):
continue
else:
nonStartStates.append(logic.PropSymbolExpr("P", x, y, 0))
startLogic = logic.to_cnf(
pacmanStart & ~(logic.associate('|', nonStartStates)))
cnf.append(startLogic)
goalState = problem.getGoalState()
stateList = []
for x in range(width + 1):
for y in range(height + 1):
if problem.isWall((x, y)):
continue
else:
stateList.append((x, y))
for time in range(maxTime):
oneStateList = []
for state in stateList:
oneStateList.append(
logic.PropSymbolExpr("P", state[0], state[1], time))
legalActionList = problem.actions(state)
illegalList = []
for action in DirectionsList:
if action in legalActionList:
nextState = problem.result(state, action)[0]
# state & action >> new state
nextLogic = (logic.PropSymbolExpr(
"P", state[0], state[1], time) & logic.PropSymbolExpr(
action, time)) >> logic.PropSymbolExpr(
'P', nextState[0], nextState[1], time + 1)
cnf.append(logic.to_cnf(nextLogic))
else:
illegalList.append(action)
for action in illegalList:
# state >> not illegal action
cnf.append(
logic.to_cnf(
logic.PropSymbolExpr('P', state[0], state[1], time) >>
~logic.PropSymbolExpr(action, time)))
# uses oneStateList, makes sure we are not in two places at once
oneState = exactlyOne(oneStateList)
cnf.append((oneState))
# Exactly 1 move per turn
Dir = []
for direction in DirectionsList:
Dir.append(logic.PropSymbolExpr(direction, time))
oneMove = exactlyOne(Dir)
cnf.append(logic.to_cnf(oneMove))
# goal state
cnf.append(logic.PropSymbolExpr("P", goalState[0], goalState[1], time))
#print time
model = logic.pycoSAT(cnf)
if model:
path = extractActionSequence(model, DirectionsList)
return path
cnf.remove(logic.PropSymbolExpr("P", goalState[0], goalState[1], time))
def get_next_action(self, observation):
# TODO : COMPLETE BY STUDENTS
# get observation for the current state and return next action to apply (and None if no action is applicable)
#self.space_kb.tell()
cleared = False
#print(self.state)
for prev_tar in self.problem[3]:
for tar in self.state[3]:
if prev_tar[0] == tar[0]:
if len(prev_tar[1]) != len(tar[1]):
self.states=[]
self.prev_fit = None
cleared=True
if cleared:
print("CLEARED")
self.problem=self.state
# Take a ship and look for the closest target+calibration
actions = self.actions(self.state)
#print(actions)
next_action = None
next_target = None
ship_missions=[]
for ship in self.state[1]:
for action in actions:
if observation.get(ship[0]) != -1:
if observation.get(ship[0]) == 1:
pos_str = 'P' + str(ship[1])
self.space_kb.tell(~logic.expr(pos_str))
elif observation.get(ship[0])==0:
pos_str='P'+str(ship[1])
self.space_kb.tell(~logic.expr(pos_str))
pos_str='P'+str((ship[1][0]+1,ship[1][1],ship[1][2]))
self.space_kb.tell(~logic.expr(pos_str))
pos_str = 'P' + str((ship[1][0]-1, ship[1][1], ship[1][2]))
self.space_kb.tell(~logic.expr(pos_str))
pos_str = 'P' + str((ship[1][0], ship[1][1]+1, ship[1][2]))
self.space_kb.tell(~logic.expr(pos_str))
pos_str = 'P' + str((ship[1][0], ship[1][1]-1, ship[1][2]))
self.space_kb.tell(~logic.expr(pos_str))
pos_str = 'P' + str((ship[1][0], ship[1][1], ship[1][2]+1))
self.space_kb.tell(~logic.expr(pos_str))
pos_str = 'P' + str((ship[1][0], ship[1][1], ship[1][2]-1))
self.space_kb.tell(~logic.expr(pos_str))
if action[0] == "use" and action [1] == ship[0]:
self.state = self.result(self.state, action)
self.states.append(self.state)
return action
if action[0] == "calibrate" and action [1] == ship[0] and ship[2][1]==False:
self.state = self.result(self.state, action)
self.states.append(self.state)
return action
if ship[2][0] is None:
if action[0] == "turn_on" and action[1] == ship[0]:
need_for_weapon = False
for tar in self.state[3]:
if action[2] in tar[1]:
need_for_weapon = True
if need_for_weapon:
self.state = self.result(self.state, action)
self.states.append(self.state)
return action
fitness = -1
tmp_min_fit=None
if observation.get(ship[0]) != -1:
ntarget = best_next_target(ship, self.state)
if ntarget != ():
fitness = ntarget[0]+observation.get(ship[0])+1
if tmp_min_fit is None:
tmp_min_fit = fitness
next_target = ntarget
if 0 < fitness < tmp_min_fit:
tmp_min_fit = fitness
next_target = ntarget
if next_target != ():
ship_missions.append((next_target,ship))
tmp_best = None
for mission in ship_missions:
if tmp_best is None:
tmp_best = mission
if 0<mission[0][0]<tmp_best[0][0]:
tmp_best = mission
'''if self.prev_fit is None:
print (mission[0][0])
self.prev_fit = mission[0][0]
elif self.prev_fit<mission[0][0]:
self.prev_fit=None
self.state = self.result(self.state, self.move_back)
return self.move_back
else:
self.prev_fit=mission[0][0]'''
if mission[1][2][0] not in mission[0][1][1]:
next_action = ("turn_on", mission[1][0], mission[0][2][0])
self.state=self.result(self.state,next_action)
return next_action
next_action = self.next_move_to_mission(mission, self.state)
if next_action is None:
return self.move_back
allow=logic.dpll_satisfiable(logic.to_cnf(logic.associate('&',self.space_kb.clauses + [logic.expr('P'+str(next_action[3]))])))
#print(allow)
tmp_state = self.result(self.state, next_action)
self.states.append(tmp_state)
while allow != False:
print('Achtung Laser')
print(allow)
next_action = self.next_move_to_mission(mission, self.state)
tmp_state = self.result(self.state, next_action)
self.states.append(tmp_state)
if len(self.states)>6:
self.states.clear()
allow = logic.dpll_satisfiable(
logic.to_cnf(logic.associate('&', self.space_kb.clauses + [logic.expr('P' + str(next_action[3]))])))
#print(allow)
self.state=tmp_state
self.move_back = (next_action[0], next_action[1], next_action[3],next_action[2])
return next_action
