in experiments/train.py [0:0]
def make_env(scenario_name, arglist, benchmark=False):
from multiagent.environment import MultiAgentEnv
import multiagent.scenarios as scenarios
# load scenario from script
scenario = scenarios.load(scenario_name + ".py").Scenario()
# create world
world = scenario.make_world()
# create multiagent environment
if benchmark:
env = MultiAgentEnv(world, scenario.reset_world, scenario.reward, scenario.observation, scenario.benchmark_data)
else:
env = MultiAgentEnv(world, scenario.reset_world, scenario.reward, scenario.observation)
return env