def beam_lin(count, room_time_limit, seed):
#beam parameters:
init_width_domain = [20]
growf_domain = [(2, 'lin'), (4, 'lin'), (8, 'lin'), (16, 'lin')]
heuristic_s = [heuristics.PowerHeuristic2(), heuristics.LinearHeuristic()]
#------------------ Create Agents ------------------
agent_list = []
for h in heuristic_s:
for init_width in init_width_domain:
for growf in growf_domain:
algorithm = AnytimeBeamSearch(init_width, growf)
agent = TestAgent(algorithm, h)
agent_list.append(agent)
#---------------- Create Roomsets --------------------
roomsets = [
c_roomsets.easy_roomset(count, seed),
c_roomsets.mild_roomset(count, seed),
c_roomsets.heavy_roomset(count, seed)
]
#---------------- measure --------------------
dbs = ameasure(agent_list, roomsets, room_time_limit)
return dbs
def beam(count, room_time_limit):
#beam parametres:
init_width_domain = [2, 6, 12]
growf_domain = [(1.1, 'exp'), (1.3, 'exp'), (2, 'lin'), (4, 'lin')]
heuristic_s = [heuristics.PowerHeuristic2(), heuristics.LinearHeuristic()]
#------------------ Create Agents ------------------
agent_list = []
for h in heuristic_s:
for init_width in init_width_domain:
for growf in growf_domain:
algorithm = AnytimeBeamSearch(init_width, growf)
agent = TestAgent(algorithm, h)
agent_list.append(agent)
#---------------- Create Roomsets --------------------
roomsets = [
c_roomsets.easy_roomset(count),
c_roomsets.heavy_roomset(count),
c_roomsets.static_rooms()
]
dbs = ameasure(agent_list, roomsets, room_time_limit)
return dbs
def test():
ag = TestAgent(AnytimeBestFirstGraphSearch(), heuristics.PowerHeuristic2())
rs = RoomSet("d")
a = ProblemSetSolution(ag, rs)
# path =r"C:\Users\inesmeya\Desktop\out\Test\p.p"
path = r"C:\Users\inesmeya\Desktop\out\Test\e.txt"
a = pload(path)
print "F"
print a
def test_algs():
from measure_core import TestAgent
from anytime_best_first import AnytimeBestFirstGraphSearch
import heuristics
import room_problems
alg = AnytimeBestFirstGraphSearch(10)
h = heuristics.PowerHeuristic2()
a = TestAgent(alg, h)
sol = a.solve3(room_problems.all_static_rooms['linear_test'], 0.5)
print sol
return sol
def best_first_depth(count, room_time_limit, seed):
''' @param count: number of rooms
'''
#beam parametres:
depths = [400]
heuristic_s = [heuristics.PowerHeuristic2()]
#------------------ Create Agents ------------------
agent_list = []
for h in heuristic_s:
for depth in depths:
algorithm = AnytimeBestFirstGraphSearch()
#algorithm = AnytimeBeamSearch(100, (2,'lin'))
agent = TestAgent(algorithm, h)
agent_list.append(agent)
#---------------- Create Roomsets --------------------
roomsets = [c_roomsets.static_rooms()]
dbs = ameasure(agent_list, roomsets, room_time_limit)
return dbs
def best_first(count, room_time_limit):
''' @param count: number of rooms
'''
#beam parametres:
depths = [10, 80, 250, 400]
heuristic_s = [heuristics.PowerHeuristic2(), heuristics.LinearHeuristic()]
#------------------ Create Agents ------------------
agent_list = []
for h in heuristic_s:
for depth in depths:
algorithm = AnytimeBestFirstGraphSearch(depth)
agent = TestAgent(algorithm, h)
agent_list.append(agent)
#---------------- Create Roomsets --------------------
roomsets = [
c_roomsets.easy_roomset(count),
c_roomsets.heavy_roomset(count),
c_roomsets.static_rooms()
]
dbs = ameasure(agent_list, roomsets, room_time_limit)
return dbs
def __init__(self):
self.heuristic = heuristics.PowerHeuristic2()
self.algo = AnytimeBeamSearch(10, (1.2, "exp"))
def __init__(self):
self.heuristic = heuristics.PowerHeuristic2()
self.algorithm = AnytimeBeamSearch(20, (1.3, 'exp'))
