def testNavigation ( self ):
distance = {
("Oradea","Zerind"): 71,
("Oradea","Sibiu"): 151,
("Neamt","Iasi"): 87,
("Zerind","Arad"): 75,
("Iasi","Vaslui"): 92,
("Arad","Sibiu"): 140,
("Arad","Timisoara"): 118,
("Sibiu","Fagaras"): 99,
("Sibiu","Rimnicu Vilcea"): 80,
("Fagaras","Bucharest"): 1211, #211,
("Vaslui","Urziceni"): 142,
("Rimnicu Vilcea","Pitesti"): 97,
("Rimnicu Vilcea","Craiova"): 146,
("Timisoara","Lugoj"): 111,
("Lugoj","Mehadia"): 70,
("Pitesti","Bucharest"): 101,
("Pitesti","Craiova"): 138,
("Hirsova","Urziceni"): 98,
("Hirsova","Eforie"): 86,
("Urcizeni","Bucharest"): 85,
("Mehadia","Drobeta"): 75,
("Bucharest","Giurgiu"): 90,
("Drobeta","Craiova"): 120,
}
sld_bucharest = {
"Arad": 366,
"Bucharest": 0,
"Craiova": 160,
"Drobeta": 242,
"Eforie": 161,
"Fagaras": 1300, #176,
"Giurgiu": 77,
"Hirsova": 151,
"Iasi": 226,
"Lugoj": 244,
"Mehadia": 241,
"Neamt": 234,
"Oradea": 380,
"Pitesti": 100,
"Rimnicu Vilcea": 193,
"Sibiu": 253,
"Timisoara": 329,
"Urcizeni": 80,
"Vaslui": 199,
"Zerind": 374,
}
def repr ( node ):
parent = ''
if not node.isInitial(): parent = node.parent().item() + ' ->'
return "%s %s (%d)" % (parent, node.item(), node.cost())
initial = "Arad"
goal = "Bucharest"
cost = lambda s, n: distance.get((s,n), distance.get((n,s))) or (s==n and 0)
successor = lambda n: [p[1-i] for p in distance for i in (0,1) if p[i] == n]
h = lambda n: sld_bucharest[n]
problem = Problem(initial, goal, successor, cost)
solver = ProblemSolver(repr)
solver.solve(problem, ProblemSolver.iterativeDeepeningGenerator(successor), True)
self.assertTrue(solver.solved(problem))
print ("Navigation: solution found using ID search: " + str(solver.solution))
print("Algorithm performance: ", solver.performance, ", memory used: ", solver.resources)
solver = ProblemSolver(repr)
solver.solve(problem, CostBasedProblemSolver.greedyBestFirstGenerator(successor, h), True)
self.assertTrue(solver.solved(problem))
print ("Navigation: solution found using greedy-best-first search: " + str(solver.solution))
print("Algorithm performance: ", solver.performance, ", memory used: ", solver.resources)
solver = CostBasedProblemSolver(repr)
solver.solve(problem, CostBasedProblemSolver.uniformCostGenerator(successor, cost))
self.assertTrue(solver.solved(problem))
print ("Navigation: solution found using uniform-cost search: " + str(solver.solution))
print("Algorithm performance: ", solver.performance, ", memory used: ", solver.resources)
solver = CostBasedProblemSolver(repr)
solver.solve(problem, CostBasedProblemSolver.aStarGenerator(successor, cost, h))
self.assertTrue(solver.solved(problem))
print ("Navigation: solution found using A*: " + str(solver.solution))
print("Algorithm performance: ", solver.performance, ", memory used: ", solver.resources)
