in experiments/train.py [0:0]
def get_trainers(env, num_adversaries, obs_shape_n, arglist):
trainers = []
model = mlp_model
trainer = MADDPGAgentTrainer
for i in range(num_adversaries):
trainers.append(trainer(
"agent_%d" % i, model, obs_shape_n, env.action_space, i, arglist,
local_q_func=(arglist.adv_policy=='ddpg')))
for i in range(num_adversaries, env.n):
trainers.append(trainer(
"agent_%d" % i, model, obs_shape_n, env.action_space, i, arglist,
local_q_func=(arglist.good_policy=='ddpg')))
return trainers