def create_emas_params(agents_count, agent_population, time_matrix, stages):
JOBS_COUNT = len(time_matrix[0])
return {
"agents": unnamed_agents(agents_count, AggregateAgent),
"aggregated_agents": lambda: flowshop_agents_initializer(agent_population, JOBS_COUNT, agents_count),
"emas": EmasService,
"minimal_energy": lambda: 0,
"reproduction_minimum": lambda: 90,
"migration_minimum": lambda: 120,
"newborn_energy": lambda: 100,
"transferred_energy": lambda: 40,
"initializer": lambda: PermutationInitializer(JOBS_COUNT),
"evaluation": lambda: FlowShopEvaluation(time_matrix),
"crossover": lambda: FirstHalfSwapsCrossover(),
"mutation": lambda: PermutationMutation(2) if stages == 0 else MemeticPermutationMutation(stages, 8, 2),
"migration": ParentMigration
}
from pyage.core.migration import Pyro4Migration
from pyage.core.statistics import TimeStatistics
from pyage.core.stop_condition import StepLimitStopCondition
from pyage.solutions.evolution.crossover import AverageFloatCrossover
from pyage.solutions.evolution.evaluation import FloatRastriginEvaluation
from pyage.solutions.evolution.initializer import FloatInitializer
from pyage.solutions.evolution.mutation import UniformFloatMutation
from pyage.solutions.evolution.selection import TournamentSelection
logger = logging.getLogger(__name__)
agents_count = int(os.environ['AGENTS'])
logger.debug("AGGREGATE, %s agents", agents_count)
agents = generate_agents("agent", agents_count, AggregateAgent)
aggregated_agents = unnamed_agents(2, Agent)
stop_condition = lambda: StepLimitStopCondition(100)
size = 500
operators = lambda: [
FloatRastriginEvaluation(),
TournamentSelection(size=55, tournament_size=30),
AverageFloatCrossover(size=size),
UniformFloatMutation(probability=0.05, radius=1)
]
initializer = lambda: FloatInitializer(500, size, -10, 10)
address_provider = address.SequenceAddressProvider
migration = Pyro4Migration
from pyage.core.stats.statistics import TimeStatistics
from pyage.core.stop_condition import StepLimitStopCondition
from pyage.solutions.evolution.crossover import AverageFloatCrossover
from pyage.solutions.evolution.evaluation import FloatRastriginEvaluation
from pyage.solutions.evolution.initializer import FloatInitializer
from pyage.solutions.evolution.mutation import UniformFloatMutation
from pyage.solutions.evolution.selection import TournamentSelection
logger = logging.getLogger(__name__)
agents_count = int(os.environ['AGENTS'])
logger.debug("AGGREGATE, %s agents", agents_count)
agents = generate_agents("agent", agents_count, AggregateAgent)
aggregated_agents = unnamed_agents(2, Agent)
stop_condition = lambda: StepLimitStopCondition(100)
size = 500
operators = lambda: [FloatRastriginEvaluation(), TournamentSelection(size=55, tournament_size=30),
AverageFloatCrossover(size=size), UniformFloatMutation(probability=0.05, radius=1)]
initializer = lambda: FloatInitializer(500, size, -10, 10)
address_provider = address.SequenceAddressProvider
migration = Pyro4Migration
locator = RandomLocator
ns_hostname = lambda: os.environ['NS_HOSTNAME']
pyro_daemon = Pyro4.Daemon()
from pyage.core.emas import EmasService
from pyage.core.locator import TorusLocator
from pyage.core.migration import ParentMigration
from pyage.core.stats.gnuplot import StepStatistics
from pyage.core.stop_condition import StepLimitStopCondition
from pyage.solutions.evolution.crossover import SinglePointCrossover
from pyage.solutions.evolution.evaluation import FloatRastriginEvaluation
from pyage.solutions.evolution.initializer import float_emas_initializer
from pyage.solutions.evolution.mutation import NormalMutation
logger = logging.getLogger(__name__)
agents_count = int(os.environ['AGENTS'])
logger.debug("EMAS, %s agents", agents_count)
agents = unnamed_agents(agents_count, AggregateAgent)
stop_condition = lambda: StepLimitStopCondition(1000)
aggregated_agents = lambda: float_emas_initializer(40, energy=100, size=50, lowerbound=-10, upperbound=10)
emas = EmasService
minimal_energy = lambda: 0
reproduction_minimum = lambda: 90
migration_minimum = lambda: 120
newborn_energy = lambda: 100
transferred_energy = lambda: 40
evaluation = FloatRastriginEvaluation
crossover = SinglePointCrossover
from pyage.core.emas import EmasService
from pyage.core.locator import TorusLocator
from pyage.core.migration import Pyro4Migration
from pyage.core.stats.statistics import NoStatistics
from pyage.core.stop_condition import StepLimitStopCondition
from pyage.solutions.evolution.crossover import SinglePointCrossover
from pyage.solutions.evolution.evaluation import FloatRastriginEvaluation
from pyage.solutions.evolution.initializer import float_emas_initializer
from pyage.solutions.evolution.mutation import NormalMutation
logger = logging.getLogger(__name__)
agents_count = int(os.environ['AGENTS'])
logger.debug("EMAS, %s agents", agents_count)
agents = unnamed_agents(agents_count, AggregateAgent)
stop_condition = lambda: StepLimitStopCondition(100)
aggregated_agents = lambda: float_emas_initializer(40, energy=100, size=50, lowerbound=-10, upperbound=10)
emas = EmasService
minimal_energy = lambda: 0
reproduction_minimum = lambda: 90
migration_minimum = lambda: 120
newborn_energy = lambda: 100
transferred_energy = lambda: 40
evaluation = FloatRastriginEvaluation
crossover = SinglePointCrossover
# Distributed environment settings
number_of_hosts = lambda: 16
global_number_of_net_agents = lambda: 16 # square root must be an integer
net_agents_per_host = lambda: global_number_of_net_agents() / number_of_hosts()
net_agents_per_line = lambda: int(sqrt(global_number_of_net_agents()))
waiting_interval = lambda: 3 # frequency of checking presence of all net_agents (in seconds)
# ================================
agents_per_net = 35
layers = lambda: [ColorLayer()]
iterations_per_update = lambda: 50
overlap_size = lambda: 5
simulate_in_overlaps = lambda: True
overlap_simulation_agent_turnaround = lambda: True
ns_hostname = lambda: os.environ['NS_HOSTNAME']
agents = net_agent(NetAgent, net_agents_per_host, net_agents_per_line,
ns_hostname)
sub_agents = unnamed_agents(agents_per_net, SubAgent)
address_provider = SequenceAddressProvider
migration = CrossBorderMigration
locator = ParentLocator
pyro_daemon = Pyro4.Daemon()
daemon = lambda: pyro_daemon
stats = lambda: PositionStatistics(
"../positions/langtons_ant_positions_%05d.txt")
