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 get_rs():
rooms_per_set = 5
num_sets = 10
ers = c_roomsets.easy_roomset(rooms_per_set, 0)
mrs = c_roomsets.mild_roomset(rooms_per_set, 0)
hrs = c_roomsets.heavy_roomset(rooms_per_set, 0)
for i in range(1, num_sets):
erst = c_roomsets.easy_roomset(rooms_per_set, i)
mrst = c_roomsets.mild_roomset(rooms_per_set, i)
hrst = c_roomsets.heavy_roomset(rooms_per_set, i)
ers.rooms.update(erst.rooms)
mrs.rooms.update(mrst.rooms)
hrs.rooms.update(hrst.rooms)
for rs in [ers, mrs, hrs]:
l1 = rs.rooms.keys()
print len(l1) #, rs.name
print sorted(l1)
return {"easy_roomset": ers, "mild_roomset": mrs, "heavy_roomset": hrs}
def get_rs():
rooms_per_set = 5
num_sets = 10
ers = c_roomsets.easy_roomset(rooms_per_set, 0)
mrs = c_roomsets.mild_roomset(rooms_per_set, 0)
hrs = c_roomsets.heavy_roomset(rooms_per_set, 0)
for i in range(1, num_sets):
erst = c_roomsets.easy_roomset(rooms_per_set, i)
mrst = c_roomsets.mild_roomset(rooms_per_set, i)
hrst = c_roomsets.heavy_roomset(rooms_per_set, i)
ers.rooms.update(erst.rooms)
mrs.rooms.update(mrst.rooms)
hrs.rooms.update(hrst.rooms)
for rs in [ers, mrs, hrs]:
l1 = rs.rooms.keys()
print len(l1)#, rs.name
print sorted(l1)
return {"easy_roomset": ers, "mild_roomset" : mrs, "heavy_roomset" : hrs}
def heavy_astar(count, room_time_limit, seed):
heuristic_s = [heuristics.PowerHeuristic2()]
# ------------------ Create Agents ------------------
agent_list = []
for h in heuristic_s:
agent = TestAgent(LimitedTimeAStar(), h)
agent_list.append(agent)
# ---------------- Create Roomsets --------------------
roomsets = [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 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 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 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 best_first_depth(count, room_time_limit, seed):
""" @param count: number of rooms
"""
# best first parameters:
depths = [10, 80, 150, 250, 400, 1000]
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, seed),
c_roomsets.mild_roomset(count, seed),
c_roomsets.heavy_roomset(count, seed),
]
dbs = ameasure(agent_list, roomsets, room_time_limit)
return dbs