def compare_searchers(problems):
searchers=[search.depth_first_tree_search,
search.depth_limited_search,
search.depth_first_graph_search,
search.breadth_first_tree_search,
search.recursive_best_first_search]
print("----- Start comparison")
print("a = total nr. of successful actions")
print("ua = of unsuccessful actions (when action() returns [])")
print("g = of goal tests")
print("hmin:hmax = nr. good states vs. bad states ")
print("s = solution")
print("t = solving time \n\n")
def do(searcher, problem):
p = InstrumentedProblem(problem)
argspec = inspect.getargspec(searcher)
if len(argspec.args) == 1:
searcher(p)
else:
searcher(p, p.h)
p.set_end_time(time.time())
return p
table = [[search.name(s)] + [do(s, problems[0])] for s in searchers]
search.print_table(table, ["Searcher", "Result"])
print("")
table = [[search.name(s)] + [do(s, problems[1])] for s in searchers]
search.print_table(table, ["Searcher", "Result with reverse number selection list"])
def compare_searchers(problems, header, searchers=[]):
best = {}
bestNode = {}
for p in problems:
best[p.label] = inf
bestNode[p.label] = None
def do(searcher, problem):
nonlocal best, bestNode
p = search.InstrumentedProblem(problem)
goalNode = searcher(p)
cost = goalNode.path_cost
if cost < best[p.label]:
best[p.label] = cost
bestNode[p.label] = goalNode
return p, cost
table = [[search.name(s)] + [do(s, p) for p in problems]
for s in searchers]
print_table(table, header)
print('----------------------------------------')
for p in problems:
bestPath = []
node = bestNode[p.label]
while node != None:
bestPath.append(node.state)
node = node.parent
summary = "Best Path for " + p.label + ": "
for state in reversed(bestPath):
try:
summary += "\n" + p.prettyPrint(state) + "\n---------"
except:
summary += " " + state
print(summary)
print('----------------------------------------')
def compare_searchers(problems, header, searchers=[]):
def do(searcher, problem):
p = search.InstrumentedProblem(problem)
goalNode = searcher(p)
return p, goalNode.path_cost
table = [[search.name(s)] + [do(s, p) for p in problems] for s in searchers]
search.print_table(table, header)
def compare_searchers(problems, header, searchers=[]):
best = {}
bestNode = {}
gradeInfo = {}
for p in problems:
best[p.label] = inf
bestNode[p.label] = None
def do(searcher, problem):
nonlocal best, bestNode, gradeInfo
ip = search.InstrumentedProblem(problem)
try:
ipLabel = ip.label
if not ipLabel in gradeInfo:
gradeInfo[ipLabel] = {}
goalNode = searcher(ip)
gradeInfo[ipLabel][searcher] = \
gradeProblem(searcher, ip, goalNode)
cost = goalNode.path_cost
if cost < best[ipLabel]:
best[ipLabel] = cost
bestNode[ipLabel] = goalNode
return ip, cost
except:
# print('searcher(' + p.label + ') raised an exception:')
# traceback.print_exc()
return ip, inf
table = [[search.name(s)] + [do(s, p) for p in problems]
for s in searchers]
print_table(table, header)
print('----------------------------------------')
for p in problems:
bestPath = []
node = bestNode[p.label]
while node != None:
bestPath.append(node.state)
node = node.parent
summary = "Best Path for " + p.label + ": "
ppFun = getattr(p, "prettyPrint", None)
if ppFun == None:
ppFun = str
ppSep = ' '
pathLength = len(bestPath)
if pathLength > 0:
stateLength = len(ppFun(bestPath[0]))
if pathLength * stateLength > 100:
ppSep = "\n"
for state in reversed(bestPath):
summary += ppSep + ppFun(state)
print(summary)
print('----------------------------------------')
return gradeInfo
def compare_searchers(problems, header, searchers=[]):
def do(searcher, problem):
p = search.InstrumentedProblem(problem)
goalNode = searcher(p)
return p, goalNode.path_cost
table = [[search.name(s)] + [do(s, p) for p in problems] for s in searchers]
search.print_table(table, header)
class GapSwitch(search.Problem):
#A 4x4 grid, each square unmarked at the start.
grid = (['U', 'U', 'U', 'U'],
['U', 'U', 'U', 'U'],
['U', 'U', 'U', 'U'],
['U', 'U', 'U', 'U'])
#defines the state using row number first, then the spaces between marked squares required in that row,
# column number, and the spaces between marked squares required in that column
state = ((2,2),(4,1))
def actions(self, state):
return ['M', 'U']
def result(self, state, action):
if action == 'up':
return 'on'
else:
return 'off'
def start(self, state, grid):
if
def goal_test(self, state):
return state == 'on'
def h(self, node):
state = node.state
if self.goal_test(state):
return 0
else:
return 1
switch_puzzle = LightSwitch('off')
switch_puzzle.label = 'Light Switch'
def compare_searchers(problems, header, searchers=[]):
best = {}
bestNode = {}
for p in problems:
best[p.label] = inf
bestNode[p.label] = None
def do(searcher, problem):
nonlocal best, bestNode
p = search.InstrumentedProblem(problem)
try:
goalNode = searcher(p)
cost = goalNode.path_cost
if cost < best[p.label]:
best[p.label] = cost
bestNode[p.label] = goalNode
return p, cost
except:
# print('searcher(' + p.label + ') raised an exception:')
# traceback.print_exc()
return p, inf
table = [[search.name(s)] + [do(s, p) for p in problems] for s in searchers]
print_table(table, header)
print('----------------------------------------')
for p in problems:
bestPath = []
node = bestNode[p.label]
while node != None:
bestPath.append(node.state)
node = node.parent
summary = "Best Path for " + p.label + ": "
for state in reversed(bestPath):
try:
summary += "\n" + p.prettyPrint(state) + "\n---------"
except:
summary += " " + str(state)
print(summary)
print('----------------------------------------')
header=hlist,
searchers=searchList
)
except:
traceback.print_exc()
allScores = newScores()
maxScores = {}
for student in gradeInfo:
print('Scores for: %s' % student)
maxScores[student] = {}
for pLabel in gradeInfo[student]:
table = []
maxScores[student][pLabel] = newScores()
for searcher in gradeInfo[student][pLabel]:
sLabel = search.name(searcher)
info = gradeInfo[student][pLabel][searcher]
scoreSet = info['score']
table.append(['%s, %s:' % (sLabel, pLabel),
scoreList(scoreSet)])
for label in scoreSet:
accumulator = accuMethods[label]
maxScores[student][pLabel][label] = accumulator(
maxScores[student][pLabel][label], scoreSet[label])
if len(table) > 1:
table.append(['%s summary:' % (pLabel),
scoreList(maxScores[student][pLabel])])
print_table(table)
if len(table) > 1:
print()
for label in allScores: