def run_large_experiment():
num_dcs = 10
num_customers = 50
num_commodities = 5
orders_per_day = 10
dcs_per_customer = 3
demand_mean = 200
demand_var = 20
num_steps = 30
num_episodes = 5
runner_random = experiment_runner.create_random_experiment_runner(
num_dcs, num_customers, dcs_per_customer, demand_mean, demand_var,
num_commodities, orders_per_day, num_steps)
runner_dqn = experiment_runner.create_dqn_experiment_runner(
num_dcs, num_customers, dcs_per_customer, demand_mean, demand_var,
num_commodities, orders_per_day, num_steps)
runner_zero = experiment_runner.create_alwayszero_experiment_runner(
num_dcs, num_customers, dcs_per_customer, demand_mean, demand_var,
num_commodities, orders_per_day, num_steps)
runner_bestfit = experiment_runner.create_bestfit_experiment_runner(
num_dcs, num_customers, dcs_per_customer, demand_mean, demand_var,
num_commodities, orders_per_day, num_steps)
#runner_random.run_episodes(num_steps, num_episodes, orders_per_day, experiment_name='dumb_agent')
runner_dqn.run_episodes(num_steps,
num_episodes,
orders_per_day,
experiment_name='dqn_agent')
def run_dqn():
print("!!!RUNNING DQN!!!")
runner_dqn = experiment_runner.create_dqn_experiment_runner(
num_dcs,
num_customers,
dcs_per_customer,
demand_mean,
demand_var,
num_commodities,
orders_per_day,
num_steps,
)
runner_dqn.run_episodes(
num_steps, num_episodes, orders_per_day, experiment_name=f"dqn_few_warehouses"
)
print("!!!DONE DQN!!!")
def two_customers_dqn_debug_run():
num_dcs = 10
num_customers = 2
num_commodities = 4
orders_per_day = 2
dcs_per_customer = 3
demand_mean = 100
demand_var = 20
num_steps = 50
num_episodes = 1000
runner_dqn = experiment_runner.create_dqn_experiment_runner(
num_dcs, num_customers, dcs_per_customer, demand_mean, demand_var,
num_commodities, orders_per_day, num_steps)
runner_dqn.run_episodes(num_steps,
num_episodes,
orders_per_day,
experiment_name='two_customers_dqn_debug')
def run_dqn():
print("!!!RUNNING DQN!!!")
reproducibility.set_seeds(0)
print("Check this array to ensure reproducibility")
print("Reproducibility DQN", np.random.randint(0, 500, size=(5, 1)))
runner_dqn = experiment_runner.create_dqn_experiment_runner(
num_dcs,
num_customers,
dcs_per_customer,
demand_mean,
demand_var,
num_commodities,
orders_per_day,
num_steps,
)
runner_dqn.run_episodes(num_steps,
num_episodes,
orders_per_day,
experiment_name=f"dqn2_few_warehouses_v3")
runner_dqn.agent.save_weights("models/dqn2_few_warehouses_v3.h5")
print("!!!DONE DQN!!!")
demand_var = 20
print("====parameters=====")
print((
num_dcs,
num_customers,
dcs_per_customer,
demand_mean,
demand_var,
num_commodities,
orders_per_day,
num_steps,
))
runner_dqn = experiment_runner.create_dqn_experiment_runner(
num_dcs,
num_customers,
dcs_per_customer,
demand_mean,
demand_var,
num_commodities,
orders_per_day,
num_steps,
)
name = f"dqn_experiment_{i}"
runner_dqn.run_episodes(num_steps,
num_episodes,
orders_per_day,
experiment_name=name)
tf.reset_default_graph()