def main_random():
env = AgarioEnv(render=RENDER,
speed_scale=SPEED_SCALE,
display_text=DISPLAY_TEXT,
grid_resolution=GRID_RESOLUTION)
agent = RandomAgent()
for episode in range(NUM_EPISODES):
state = env.reset()
num_steps = 0
done = False
while True:
action = agent.get_action(state)
for _ in range(NUM_SKIP_FRAMES):
if RENDER:
env.render()
state, reward, done, _ = env.step(action)
if done or num_steps >= MAX_STEPS:
print(f'epoch: {episode}, max_mass = {state.mass}')
agent.max_masses.append(state.mass)
break
num_steps += 1
agent.save_performance(path='random.performance')
agent.print_final_stats()
env.close()
def close(self):
if (self.physics_connected):
p.disconnect()
self.physics_connected = False
if __name__ == "__main__":
env = BoosterBackEnv(render=True)
epds = 3
#agent = LSTMAgent()
#agent = MaxThrustAgent()
agent = RandomAgent()
#agent = DoNothingAgent()
for epd in range(epds):
obs = env.reset()
done = False
while not done:
action = agent.get_action(obs)
time.sleep(0.01)
obs, reward, done, info = env.step(action)
import pdb; pdb.set_trace()
