Spaces:
Sleeping
Sleeping
File size: 1,222 Bytes
e0c3c75 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
import multiprocessing
import time
import gymnasium as gym
import numpy as np
from gymnasium.envs.toy_text.frozen_lake import generate_random_map
import wandb
from DPAgent import DPAgent
from MCAgent import MCAgent
env_ver = "FrozenLake-v1"
def test_dp(gamma=0.99):
env = gym.make(
env_ver,
render_mode="ansi",
# desc=generate_random_map(8, seed=3141),
# is_slippery=False,
)
dp = DPAgent(env=env_ver, gamma=0.99)
dp.env = env
dp.env_name = env_ver
dp.V = np.zeros(dp.env.observation_space.n)
dp.Pi = np.zeros(dp.env.observation_space.n, dp.env.action_space.n)
dp.n_states, dp.n_actions = (
dp.env.observation_space.n,
dp.env.action_space.n,
)
times = dp.train()
# np.save(f"times_{gamma}.npy", times)
s = env.render()
print(s)
def main():
wandb.init(
project="cs581",
# job_type=args.wandb_job_type,
# config=dict(args._get_kwargs()),
)
np.set_printoptions(linewidth=500, precision=3)
# with multiprocessing.Pool(8) as p:
# gamma = [0.99, 0.95, 0.9, 0.8, 0.7, 0.6, 0.5, 0.1]
# p.map(test_dp, gamma)
test_dp(0.99)
if __name__ == "__main__":
main()
|