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ia-guiao-sobre-pesquisa
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247
cidades.py
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@ -1,130 +1,119 @@
# #
# Module: cidades # Module: cidades
# #
# Implements a SearchDomain for find paths between cities # Implements a SearchDomain for find paths between cities
# using the tree_search module # using the tree_search module
# #
# (c) Luis Seabra Lopes # (c) Luis Seabra Lopes
# Introducao a Inteligencia Artificial, 2012-2020 # Introducao a Inteligencia Artificial, 2012-2020
# Inteligência Artificial, 2014-2023 # Inteligência Artificial, 2014-2023
# #
from tree_search import * from tree_search import *
class Cidades(SearchDomain): class Cidades(SearchDomain):
def __init__(self,connections, coordinates): def __init__(self,connections, coordinates):
self.connections = connections self.connections = connections
self.coordinates = coordinates self.coordinates = coordinates
def actions(self,city):
def actions(self,city): actlist = []
actlist = [] for (C1,C2,D) in self.connections:
for (C1,C2,D) in self.connections: if (C1==city):
if (C1==city): actlist += [(C1,C2)]
actlist += [(C1,C2)] elif (C2==city):
elif (C2==city): actlist += [(C2,C1)]
actlist += [(C2,C1)] return actlist
return actlist def result(self,city,action):
(C1,C2) = action
def result(self,city,action): if C1==city:
(C1,C2) = action return C2
if C1==city: def cost(self, city, action):
return C2 pass
def heuristic(self, city, goal_city):
def cost(self, city, action): pass
(C1,C2) = action def satisfies(self, city, goal_city):
for (X,Y,D) in self.connections: return goal_city==city
if X==C1 and Y==C2:
return D
if X==C2 and Y==C1: cidades_portugal = Cidades(
return D # Ligacoes por estrada
[
def heuristic(self, city, goal_city): ('Coimbra', 'Leiria', 73),
coords_city = cidades_portugal.coordinates[city] ('Aveiro', 'Agueda', 35),
coords_goal_city = cidades_portugal.coordinates[goal_city] ('Porto', 'Agueda', 79),
('Agueda', 'Coimbra', 45),
return ((coords_city[0] - coords_goal_city[0])**2 + (coords_city[1] - coords_goal_city[1])**2)**0.5 ('Viseu', 'Agueda', 78),
('Aveiro', 'Porto', 78),
def satisfies(self, city, goal_city): ('Aveiro', 'Coimbra', 65),
return goal_city==city ('Figueira', 'Aveiro', 77),
('Braga', 'Porto', 57),
('Viseu', 'Guarda', 75),
cidades_portugal = Cidades( ('Viseu', 'Coimbra', 91),
# Ligacoes por estrada ('Figueira', 'Coimbra', 52),
[ ('Leiria', 'Castelo Branco', 169),
('Coimbra', 'Leiria', 73), ('Figueira', 'Leiria', 62),
('Aveiro', 'Agueda', 35), ('Leiria', 'Santarem', 78),
('Porto', 'Agueda', 79), ('Santarem', 'Lisboa', 82),
('Agueda', 'Coimbra', 45), ('Santarem', 'Castelo Branco', 160),
('Viseu', 'Agueda', 78), ('Castelo Branco', 'Viseu', 174),
('Aveiro', 'Porto', 78), ('Santarem', 'Evora', 122),
('Aveiro', 'Coimbra', 65), ('Lisboa', 'Evora', 132),
('Figueira', 'Aveiro', 77), ('Evora', 'Beja', 105),
('Braga', 'Porto', 57), ('Lisboa', 'Beja', 178),
('Viseu', 'Guarda', 75), ('Faro', 'Beja', 147),
('Viseu', 'Coimbra', 91), # extra
('Figueira', 'Coimbra', 52), ('Braga', 'Guimaraes', 25),
('Leiria', 'Castelo Branco', 169), ('Porto', 'Guimaraes', 44),
('Figueira', 'Leiria', 62), ('Guarda', 'Covilha', 46),
('Leiria', 'Santarem', 78), ('Viseu', 'Covilha', 57),
('Santarem', 'Lisboa', 82), ('Castelo Branco', 'Covilha', 62),
('Santarem', 'Castelo Branco', 160), ('Guarda', 'Castelo Branco', 96),
('Castelo Branco', 'Viseu', 174), ('Lamego','Guimaraes', 88),
('Santarem', 'Evora', 122), ('Lamego','Viseu', 47),
('Lisboa', 'Evora', 132), ('Lamego','Guarda', 64),
('Evora', 'Beja', 105), ('Portalegre','Castelo Branco', 64),
('Lisboa', 'Beja', 178), ('Portalegre','Santarem', 157),
('Faro', 'Beja', 147), ('Portalegre','Evora', 194) ],
# extra
('Braga', 'Guimaraes', 25), # City coordinates
('Porto', 'Guimaraes', 44), { 'Aveiro': (41,215),
('Guarda', 'Covilha', 46), 'Figueira': ( 24, 161),
('Viseu', 'Covilha', 57), 'Coimbra': ( 60, 167),
('Castelo Branco', 'Covilha', 62), 'Agueda': ( 58, 208),
('Guarda', 'Castelo Branco', 96), 'Viseu': ( 104, 217),
('Lamego','Guimaraes', 88), 'Braga': ( 61, 317),
('Lamego','Viseu', 47), 'Porto': ( 45, 272),
('Lamego','Guarda', 64), 'Lisboa': ( 0, 0),
('Portalegre','Castelo Branco', 64), 'Santarem': ( 38, 59),
('Portalegre','Santarem', 157), 'Leiria': ( 28, 115),
('Portalegre','Evora', 194) ], 'Castelo Branco': ( 140, 124),
'Guarda': ( 159, 204),
# City coordinates 'Evora': (120, -10),
{ 'Aveiro': (41,215), 'Beja': (125, -110),
'Figueira': ( 24, 161), 'Faro': (120, -250),
'Coimbra': ( 60, 167), #extra
'Agueda': ( 58, 208), 'Guimaraes': ( 71, 300),
'Viseu': ( 104, 217), 'Covilha': ( 130, 175),
'Braga': ( 61, 317), 'Lamego' : (125,250),
'Porto': ( 45, 272), 'Portalegre': (130,170) }
'Lisboa': ( 0, 0), )
'Santarem': ( 38, 59),
'Leiria': ( 28, 115),
'Castelo Branco': ( 140, 124),
'Guarda': ( 159, 204),
'Evora': (120, -10), p = SearchProblem(cidades_portugal,'Braga','Faro')
'Beja': (125, -110), t = SearchTree(p,'breadth')
'Faro': (120, -250),
#extra print(t.search())
'Guimaraes': ( 71, 300),
'Covilha': ( 130, 175),
'Lamego' : (125,250), # Atalho para obter caminho de c1 para c2 usando strategy:
'Portalegre': (130,170) } def search_path(c1,c2,strategy):
) my_prob = SearchProblem(cidades_portugal,c1,c2)
my_tree = SearchTree(my_prob)
my_tree.strategy = strategy
return my_tree.search()
p = SearchProblem(cidades_portugal,'Braga','Faro')
t = SearchTree(p,'breadth')
print(t.search())
# Atalho para obter caminho de c1 para c2 usando strategy:
def search_path(c1,c2,strategy):
my_prob = SearchProblem(cidades_portugal,c1,c2)
my_tree = SearchTree(my_prob)
my_tree.strategy = strategy
return my_tree.search()

39
tree_search.py
View File

@ -62,16 +62,12 @@ class SearchProblem:
# Nos de uma arvore de pesquisa # Nos de uma arvore de pesquisa
class SearchNode: class SearchNode:
def __init__(self,state,parent, depth, cost=0, heuristic=0): def __init__(self,state,parent, depth):
self.state = state self.state = state
self.parent = parent self.parent = parent
self.depth = depth self.depth = depth
self.cost = cost
self.heuristic = heuristic
def __str__(self): def __str__(self):
return "no(" + str(self.state) + "," + str(self.parent) + ")" return "no(" + str(self.state) + "," + str(self.parent) + ")"
def __repr__(self): def __repr__(self):
return str(self) return str(self)
@ -87,8 +83,6 @@ class SearchTree:
self.solution = None self.solution = None
self.terminals = 0 self.terminals = 0
self.non_terminals = 0 self.non_terminals = 0
self.highest_cost_nodes = [root]
self.average_depth = 0
@property @property
def length(self): def length(self):
@ -98,10 +92,6 @@ class SearchTree:
def avg_branching(self): def avg_branching(self):
return ((self.terminals + self.non_terminals) - 1) / self.non_terminals if self.non_terminals > 0 else None return ((self.terminals + self.non_terminals) - 1) / self.non_terminals if self.non_terminals > 0 else None
@property
def cost(self):
return self.solution.cost if self.solution else None
# obter o caminho (sequencia de estados) da raiz ate um no # obter o caminho (sequencia de estados) da raiz ate um no
def get_path(self,node): def get_path(self,node):
if node.parent == None: if node.parent == None:
@ -115,10 +105,8 @@ class SearchTree:
while self.open_nodes != []: while self.open_nodes != []:
self.terminals = len(self.open_nodes) self.terminals = len(self.open_nodes)
node = self.open_nodes.pop(0) node = self.open_nodes.pop(0)
if self.problem.goal_test(node.state): if self.problem.goal_test(node.state):
self.solution = node self.solution = node
self.average_depth = self.average_depth / (self.terminals + self.non_terminals)
return self.get_path(node) return self.get_path(node)
self.non_terminals += 1 self.non_terminals += 1
@ -126,22 +114,13 @@ class SearchTree:
for a in self.problem.domain.actions(node.state): for a in self.problem.domain.actions(node.state):
newstate = self.problem.domain.result(node.state,a) newstate = self.problem.domain.result(node.state,a)
if newstate not in self.get_path(node): if newstate not in self.get_path(node):
newnode = SearchNode( newnode = SearchNode(newstate,node,node.depth+1)
newstate, if limit != None and self.strategy == 'depth':
node, if newnode.depth <= limit:
node.depth+1, lnewnodes.append(newnode)
node.cost+self.problem.domain.cost(node.state,a), else:
self.problem.domain.heuristic(newstate,self.problem.goal)
)
if not (limit != None and self.strategy == 'depth' and newnode.depth > limit):
lnewnodes.append(newnode) lnewnodes.append(newnode)
if newnode.cost > self.highest_cost_nodes[0].cost:
self.highest_cost_nodes = [newnode]
elif newnode.cost == self.highest_cost_nodes[0].cost:
self.highest_cost_nodes.append(newnode)
self.average_depth += newnode.depth
self.add_to_open(lnewnodes) self.add_to_open(lnewnodes)
return None return None
# juntar novos nos a lista de nos abertos de acordo com a estrategia # juntar novos nos a lista de nos abertos de acordo com a estrategia
@ -151,9 +130,5 @@ class SearchTree:
elif self.strategy == 'depth': elif self.strategy == 'depth':
self.open_nodes[:0] = lnewnodes self.open_nodes[:0] = lnewnodes
elif self.strategy == 'uniform': elif self.strategy == 'uniform':
self.open_nodes = sorted(self.open_nodes + lnewnodes, key=lambda node: node.cost) pass
elif self.strategy == 'greedy':
self.open_nodes = sorted(self.open_nodes + lnewnodes, key=lambda node: node.heuristic)
elif self.strategy == 'a*':
self.open_nodes = sorted(self.open_nodes + lnewnodes, key=lambda node: node.cost + node.heuristic)