class local_env(object):
def __init__(self, env_id):
remote_base = 'http://127.0.0.1:5000'
self.client = Client(remote_base)
self.instance_id = self.client.env_create(env_id)
def reset(self):
obs = self.client.env_reset(self.instance_id)
return obs
def step(self, action):
#print("---sssss---------",type(action),action.item())
[observation, reward, done,
info] = self.client.env_step(self.instance_id, action.item(), True)
return observation, reward, done, info
def action_space_sample(self):
action = self.client.env_action_space_sample(self.instance_id)
return action
def action_space_info(self):
info = self.client.env_action_space_info(self.instance_id)
return info
def observation_space_info(self):
info = self.client.env_observation_space_info(self.instance_id)
return info
from gym_http_client import Client
class RandomDiscreteAgent(object):
def __init__(self, n):
self.n = n
def act(self, observation, reward, done):
return np.random.randint(self.n)
if __name__ == '__main__':
logger = logging.getLogger()
logger.setLevel(logging.INFO)
# Set up client
remote_base = 'http://127.0.0.1:5000'
client = Client(remote_base)
# Set up environment
env_id = 'CartPole-v0'
instance_id = client.env_create(env_id)
# Set up agent
action_space_info = client.env_action_space_info(instance_id)
agent = RandomDiscreteAgent(action_space_info['n'])
# Run experiment, with monitor
outdir = '/tmp/random-agent-results'
client.env_monitor_start(instance_id, outdir, force=True)
episode_count = 100
max_steps = 200
class RandomDiscreteAgent(object):
def __init__(self, n):
self.n = n
def act(self, observation, reward, done):
return np.random.randint(self.n)
if __name__ == '__main__':
logger = logging.getLogger()
logger.setLevel(logging.INFO)
# Set up client
remote_base = 'http://127.0.0.1:5000'
client = Client(remote_base)
# Set up environment
env_id = 'CartPole-v0'
instance_id = client.env_create(env_id)
# Set up agent
action_space_info = client.env_action_space_info(instance_id)
agent = RandomDiscreteAgent(action_space_info['n'])
# Run experiment, with monitor
outdir = '/tmp/random-agent-results'
client.env_monitor_start(instance_id,
outdir,
force=True,
resume=False,
def __init__(self, env_id):
remote_base = 'http://127.0.0.1:5000'
self.client = Client(remote_base)
self.instance_id = self.client.env_create(env_id)
import logging
from gym_http_client import Client
class RandomDiscreteAgent(object):
def __init__(self, n):
self.n = n
if __name__ == '__main__':
logger = logging.getLogger()
logger.setLevel(logging.INFO)
# Set up client
remote_base = 'http://127.0.0.1:5000'
client = Client(remote_base)
# Set up environment
env_id = 'CartPole-v0'
instance_id = client.env_create(env_id)
# Set up agent
action_space_info = client.env_action_space_info(instance_id)
agent = RandomDiscreteAgent(action_space_info['n'])
# Run experiment, with monitor
outdir = '/tmp/random-agent-results'
client.env_monitor_start(instance_id, outdir, force=True, resume=False, video_callable=False)
episode_count = 100
max_steps = 200
reward = 0
class RandomDiscreteAgent(object):
def __init__(self, n):
self.n = n
def act(self, observation, reward, done):
return np.random.randint(self.n)
if __name__ == '__main__':
logger = logging.getLogger()
logger.setLevel(logging.INFO)
# Set up client
remote_base = 'http://127.0.0.1:5000'
client = Client(remote_base)
# Set up environment
env_id = 'CartPole-v0'
instance_id = client.env_create(env_id)
# Set up agent
action_space_info = client.env_action_space_info(instance_id)
agent = RandomDiscreteAgent(action_space_info['n'])
# Run experiment, with monitor
outdir = '/tmp/random-agent-results'
client.env_monitor_start(instance_id, outdir, force=True)
episode_count = 100
max_steps = 200