diff --git a/gui/romania_problem.py b/gui/romania_problem.py
index 11eebaaf8..f13c7a1f5 100644
--- a/gui/romania_problem.py
+++ b/gui/romania_problem.py
@@ -5,7 +5,7 @@
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
from search import *
from search import breadth_first_tree_search as bfts, depth_first_tree_search as dfts, \
- depth_first_graph_search as dfgs, breadth_first_search as bfs
+ depth_first_graph_search as dfgs, breadth_first_search as bfs, uniform_cost_search as ucs
from utils import Stack, FIFOQueue, PriorityQueue
from copy import deepcopy
@@ -163,7 +163,7 @@ def create_map(root):
romania_locations['Pitesti'][0],
height -
romania_locations['Pitesti'][1],
- romania_map.get('Bucharest', 'Pitesti'))
+ romania_map.get('Bucharest', 'Pitesti'))
make_line(
city_map,
romania_locations['Fagaras'][0],
@@ -284,7 +284,7 @@ def make_rectangle(map, x0, y0, margin, city_name):
y0 - 2 * margin,
text=city_name,
anchor=E)
- else:
+ else:
map.create_text(
x0 - 2 * margin,
y0 - 2 * margin,
@@ -446,7 +446,7 @@ def breadth_first_search(problem):
node = frontier.pop()
display_current(node)
explored.add(node.state)
- if counter % 3 == 1 and counter >= 0:
+ if counter % 3 == 1 and counter >= 0:
for child in node.expand(problem):
if child.state not in explored and child not in frontier:
if problem.goal_test(child.state):
@@ -466,9 +466,55 @@ def depth_first_graph_search(problem):
return graph_search(problem)
+def best_first_graph_search(problem, f):
+ """Search the nodes with the lowest f scores first.
+ You specify the function f(node) that you want to minimize; for example,
+ if f is a heuristic estimate to the goal, then we have greedy best
+ first search; if f is node.depth then we have breadth-first search.
+ There is a subtlety: the line "f = memoize(f, 'f')" means that the f
+ values will be cached on the nodes as they are computed. So after doing
+ a best first search you can examine the f values of the path returned."""
+ global frontier, node, explored, counter
+
+ if counter == -1:
+ f = memoize(f, 'f')
+ node = Node(problem.initial)
+ display_current(node)
+ if problem.goal_test(node.state):
+ return node
+ frontier = PriorityQueue(min, f)
+ frontier.append(node)
+ display_frontier(frontier)
+ explored = set()
+ if counter % 3 == 0 and counter >= 0:
+ node = frontier.pop()
+ display_current(node)
+ if problem.goal_test(node.state):
+ return node
+ explored.add(node.state)
+ if counter % 3 == 1 and counter >= 0:
+ for child in node.expand(problem):
+ if child.state not in explored and child not in frontier:
+ frontier.append(child)
+ elif child in frontier:
+ incumbent = frontier[child]
+ if f(child) < f(incumbent):
+ del frontier[incumbent]
+ frontier.append(child)
+ display_frontier(frontier)
+ if counter % 3 == 2 and counter >= 0:
+ display_explored(node)
+ return None
+
+
+def uniform_cost_search(problem):
+ """[Figure 3.14]"""
+ return best_first_graph_search(problem, lambda node: node.path_cost)
+
+
# TODO:
# Remove redundant code.
-# Make the interchangbility work between various algorithms at each step.
+# Make the interchangbility work between various algorithms at each step.
def on_click():
'''
This function defines the action of the 'Next' button.
@@ -507,6 +553,14 @@ def on_click():
display_final(final_path)
next_button.config(state="disabled")
counter += 1
+ elif "Uniform Cost Search" == algo.get():
+ node = uniform_cost_search(romania_problem)
+ if node is not None:
+ final_path = ucs(romania_problem).solution()
+ final_path.append(start.get())
+ display_final(final_path)
+ next_button.config(state="disabled")
+ counter += 1
def reset_map():
@@ -532,9 +586,10 @@ def main():
goal.set('Bucharest')
cities = sorted(romania_map.locations.keys())
algorithm_menu = OptionMenu(
- root,
+ root,
algo, "Breadth-First Tree Search", "Depth-First Tree Search",
- "Breadth-First Search", "Depth-First Graph Search")
+ "Breadth-First Search", "Depth-First Graph Search",
+ "Uniform Cost Search")
Label(root, text="\n Search Algorithm").pack()
algorithm_menu.pack()
Label(root, text="\n Start City").pack()
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