def main():
args = parser.parse_args()
bounds, ghosts, pacman, goal = mapPositions(args.layout)
print('Barreiras:', bounds)
print('Fantasmas:', ghosts)
print('Pacman:', pacman)
print('Gol:', goal)
print()
#Problema e algoritmos
problem = PacmanProblem(obstacles=bounds | ghosts,
initial=pacman,
goal=goal)
gfsProblem = greedy_best_first_search(problem)
astarProblem = astar_search(problem)
bfsProblem = breadth_first_graph_search(problem)
dfsProblem = depth_first_graph_search(problem)
print('Greedy Best First Search:')
print('Caminho:', gfsProblem.path())
print('Gol:', gfsProblem)
print('A* Search:')
print('Caminho:', astarProblem.path())
print('Gol:', astarProblem)
print('Breadth-First Search:')
print('Caminho:', bfsProblem.path())
print('Gol:', dfsProblem)
print('Depth-First Search:')
print('Caminho:', dfsProblem.path())
print('Gol:', dfsProblem)
print()
print('Gerando saídas...')
generateOutput(gfsProblem.path(), args.layout, 'gfs')
generateOutput(astarProblem.path(), args.layout, 'astar')
generateOutput(dfsProblem.path(), args.layout, 'bfs')
generateOutput(dfsProblem.path(), args.layout, 'dfs')
print()
print('Desempenho:')
report([
greedy_best_first_search, astar_search, breadth_first_graph_search,
depth_first_graph_search
], [problem])
print("Running UNIFORM-COST-TREE-SEARCH")
print('-' * 50)
ucts = uniform_cost_search(ep, search_type=best_first_tree_search)
print("Solution", ucts.solution())
print()
print('-' * 50)
print(
"Running GREEDY-BEST-FIRST-TREE-SEARCH USING # MISPLACED TILES HEURISTIC"
)
print('-' * 50)
gbfts = greedy_best_first_search(ep,
misplaced_tiles_heuristic,
search_type=best_first_tree_search)
print("Solution", gbfts.solution())
print()
print('-' * 50)
print("Running A*-TREE-SEARCH USING # MISPLACED TILES HEURISTIC")
print('-' * 50)
asts = astar_search(ep,
misplaced_tiles_heuristic,
search_type=best_first_tree_search)
print("Solution", asts.solution())
import search
from graph import Graph
if __name__ == "__main__":
# Setting graph we initiated to search class...
graph = Graph()
search.graph = graph
search.depth_first_search()
search.breath_first_search()
search.iterative_deepening_search()
search.uniform_cost_search()
search.greedy_best_first_search()
search.a_star_search()
print()
print('-' * 50)
print("Q3: UNIFORM-COST-GRAPH-SEARCH")
print('-' * 50)
ucs = uniform_cost_search(travel_problem,
search_type=best_first_graph_search)
print("Solution", ucs.solution())
print()
print('-' * 50)
print("Q4: GREEDY-BEST-FIRST-TREE-SEARCH")
print('-' * 50)
gbfs = greedy_best_first_search(travel_problem,
city_h,
search_type=best_first_tree_search)
print("Solution", gbfs.solution())
print()
print('-' * 50)
print("Q5: A*-TREE-SEARCH")
print('-' * 50)
asts = astar_search(travel_problem,
city_h,
search_type=best_first_tree_search)
print("Solution", asts.solution())
def main():
args = parser.parse_args()
bounds, ghosts, pacman, goal = mapPositions(args.layout)
print('Barreiras:', bounds)
print('Fantasmas:', ghosts)
print('Pacman:', pacman)
print('Gol:', goal)
print()
#Problema e algoritmos
problem = PacmanProblem(obstacles=bounds | ghosts,
initial=pacman,
goal=goal)
gfsProblem = greedy_best_first_search(problem)
astarProblem = astar_search(problem)
bfsProblem = breadth_first_graph_search(problem)
dfsProblem = depth_first_graph_search(problem)
hcProblem = hill_climbing(problem)
print('Greedy Best First Search:')
print('Caminho:', gfsProblem.path())
print('Gol:', gfsProblem)
print('A* Search:')
print('Caminho:', astarProblem.path())
print('Solução:', astarProblem.solution())
print('Estados:', path_states(astarProblem))
print('Gol:', astarProblem)
print('Breadth-First Search:')
print('Caminho:', bfsProblem.path())
print('Solução:', bfsProblem.solution())
print('Estados:', path_states(bfsProblem))
print('Gol:', dfsProblem)
print('Depth-First Search:')
print('Caminho:', dfsProblem.path())
print('Solução:', dfsProblem.solution())
print('Estados:', path_states(dfsProblem))
print('Gol:', dfsProblem)
print('Hill Climbing:')
print('Caminho:', hcProblem.path())
print('Solução:', hcProblem.solution())
print('Estados:', path_states(hcProblem))
print('Gol:', dfsProblem)
print()
print('Gerando saídas...')
generateOutput(
set(gfsProblem.solution()) - {pacman, goal},
gfsProblem.explored - {pacman, goal}, args.layout, 'gfs')
generateOutput(
set(astarProblem.solution()) - {pacman, goal},
astarProblem.explored - {pacman, goal}, args.layout, 'astar')
generateOutput(
set(bfsProblem.solution()) - {pacman, goal},
bfsProblem.explored - {pacman, goal}, args.layout, 'bfs')
generateOutput(
set(dfsProblem.solution()) - {pacman, goal},
dfsProblem.explored - {pacman, goal}, args.layout, 'dfs')
generateOutput(
set(hcProblem.solution()) - {pacman, goal},
hcProblem.explored - {pacman, goal}, args.layout, 'hc')
print()
print('Desempenho:')
report([
greedy_best_first_search, astar_search, breadth_first_graph_search,
depth_first_graph_search, hill_climbing
], [problem])
print print '-' * 50 print "Running UNIFORM-COST-TREE-SEARCH" print '-' * 50 ucts = uniform_cost_search(ep, search_type=best_first_tree_search) print "Solution", ucts.solution() print print '-' * 50 print "Running GREEDY-BEST-FIRST-TREE-SEARCH USING # MISPLACED TILES HEURISTIC" print '-' * 50 gbfts = greedy_best_first_search(ep, misplaced_tiles_heuristic, search_type=best_first_tree_search) print "Solution", gbfts.solution() print print '-' * 50 print "Running A*-TREE-SEARCH USING # MISPLACED TILES HEURISTIC" print '-' * 50 asts = astar_search(ep, misplaced_tiles_heuristic, search_type=best_first_tree_search) print "Solution", asts.solution() print print '=' * 50 print '=' * 50
print
print '-' * 50
print "Running UNIFORM-COST-GRAPH-SEARCH"
print '-' * 50
ucs = uniform_cost_search(travel_problem, search_type=best_first_graph_search)
print "Solution", ucs.solution()
print
print '-' * 50
print "Running GREEDY-BEST-FIRST-TREE-SEARCH"
print '-' * 50
gbfs = greedy_best_first_search(travel_problem, city_h, search_type=best_first_tree_search)
print "Solution", gbfs.solution()
print
print '-' * 50
print "Running A*-TREE-SEARCH"
print '-' * 50
asts = astar_search(travel_problem, city_h, search_type=best_first_tree_search)
print "Solution", asts.solution()
print
print '=' * 50