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更新算法模版

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johnjim0816
2022-11-06 12:15:36 +08:00
parent 466a17707f
commit dc78698262
256 changed files with 17282 additions and 10229 deletions
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19
projects/codes/Sarsa/Test_CliffWalking-v0_Sarsa_20221030-021206/config.yaml Normal file
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general_cfg:
algo_name: Sarsa
device: cpu
env_name: CliffWalking-v0
load_checkpoint: true
load_path: Train_CliffWalking-v0_Sarsa_20221030-021146
max_steps: 200
mode: test
save_fig: true
seed: 1
show_fig: false
test_eps: 20
train_eps: 400
algo_cfg:
epsilon_decay: 300
epsilon_end: 0.01
epsilon_start: 0.95
gamma: 0.95
lr: 0.1

24
projects/codes/Sarsa/Test_CliffWalking-v0_Sarsa_20221030-021206/logs/log.txt Normal file
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2022-10-30 02:12:06 - r - INFO: - n_states: 48, n_actions: 4
2022-10-30 02:12:06 - r - INFO: - Start testing!
2022-10-30 02:12:06 - r - INFO: - Env: CliffWalking-v0, Algorithm: Sarsa, Device: cpu
2022-10-30 02:12:06 - r - INFO: - Episode: 1/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 2/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 3/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 4/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 5/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 6/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 7/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 8/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 9/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 10/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 11/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 12/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 13/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 14/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 15/20, Reward: -15.00, Steps:15
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2022-10-30 02:12:06 - r - INFO: - Episode: 17/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 18/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 19/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Episode: 20/20, Reward: -15.00, Steps:15
2022-10-30 02:12:06 - r - INFO: - Finish testing!

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projects/codes/Sarsa/outputs/CliffWalking-v0/20220825-213316/results/testing_results.csv → projects/codes/Sarsa/Test_CliffWalking-v0_Sarsa_20221030-021206/results/res.csv
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projects/codes/Sarsa/Test_Racetrack-v0_Sarsa_20221030-021347/config.yaml Normal file
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general_cfg:
algo_name: Sarsa
device: cpu
env_name: Racetrack-v0
load_checkpoint: true
load_path: Train_Racetrack-v0_Sarsa_20221030-021315
max_steps: 200
mode: test
save_fig: true
seed: 10
show_fig: false
test_eps: 20
train_eps: 400
algo_cfg:
epsilon_decay: 200
epsilon_end: 0.01
epsilon_start: 0.9
gamma: 0.99
lr: 0.1

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projects/codes/Sarsa/Test_Racetrack-v0_Sarsa_20221030-021347/logs/log.txt Normal file
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2022-10-30 02:13:47 - r - INFO: - n_states: 4, n_actions: 9
2022-10-30 02:13:47 - r - INFO: - Start testing!
2022-10-30 02:13:47 - r - INFO: - Env: Racetrack-v0, Algorithm: Sarsa, Device: cpu
2022-10-30 02:13:47 - r - INFO: - Episode: 1/20, Reward: 3.00, Steps:7
2022-10-30 02:13:47 - r - INFO: - Episode: 2/20, Reward: 3.00, Steps:7
2022-10-30 02:13:47 - r - INFO: - Episode: 3/20, Reward: 2.00, Steps:8
2022-10-30 02:13:47 - r - INFO: - Episode: 4/20, Reward: 3.00, Steps:7
2022-10-30 02:13:47 - r - INFO: - Episode: 5/20, Reward: -12.00, Steps:12
2022-10-30 02:13:47 - r - INFO: - Episode: 6/20, Reward: -49.00, Steps:29
2022-10-30 02:13:47 - r - INFO: - Episode: 7/20, Reward: 3.00, Steps:7
2022-10-30 02:13:47 - r - INFO: - Episode: 8/20, Reward: -17.00, Steps:17
2022-10-30 02:13:47 - r - INFO: - Episode: 9/20, Reward: 4.00, Steps:6
2022-10-30 02:13:47 - r - INFO: - Episode: 10/20, Reward: -17.00, Steps:17
2022-10-30 02:13:47 - r - INFO: - Episode: 11/20, Reward: 2.00, Steps:8
2022-10-30 02:13:47 - r - INFO: - Episode: 12/20, Reward: 3.00, Steps:7
2022-10-30 02:13:47 - r - INFO: - Episode: 13/20, Reward: 3.00, Steps:7
2022-10-30 02:13:47 - r - INFO: - Episode: 14/20, Reward: 2.00, Steps:8
2022-10-30 02:13:47 - r - INFO: - Episode: 15/20, Reward: 3.00, Steps:7
2022-10-30 02:13:47 - r - INFO: - Episode: 16/20, Reward: -34.00, Steps:24
2022-10-30 02:13:47 - r - INFO: - Episode: 17/20, Reward: 3.00, Steps:7
2022-10-30 02:13:47 - r - INFO: - Episode: 18/20, Reward: 5.00, Steps:5
2022-10-30 02:13:47 - r - INFO: - Episode: 19/20, Reward: 5.00, Steps:5
2022-10-30 02:13:47 - r - INFO: - Episode: 20/20, Reward: 3.00, Steps:7
2022-10-30 02:13:47 - r - INFO: - Finish testing!

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projects/codes/Sarsa/Test_Racetrack-v0_Sarsa_20221030-021347/results/res.csv Normal file
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episodes,rewards,steps
0,3,7
1,3,7
2,2,8
3,3,7
4,-12,12
5,-49,29
6,3,7
7,-17,17
8,4,6
9,-17,17
10,2,8
11,3,7
12,3,7
13,2,8
14,3,7
15,-34,24
16,3,7
17,5,5
18,5,5
19,3,7
1 episodes rewards steps
2 0 3 7
3 1 3 7
4 2 2 8
5 3 3 7
6 4 -12 12
7 5 -49 29
8 6 3 7
9 7 -17 17
10 8 4 6
11 9 -17 17
12 10 2 8
13 11 3 7
14 12 3 7
15 13 2 8
16 14 3 7
17 15 -34 24
18 16 3 7
19 17 5 5
20 18 5 5
21 19 3 7

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projects/codes/Sarsa/Train_CliffWalking-v0_Sarsa_20221030-021146/config.yaml Normal file
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general_cfg:
algo_name: Sarsa
device: cpu
env_name: CliffWalking-v0
load_checkpoint: false
load_path: Train_CartPole-v1_DQN_20221026-054757
max_steps: 200
mode: train
save_fig: true
seed: 1
show_fig: false
test_eps: 20
train_eps: 800
algo_cfg:
epsilon_decay: 300
epsilon_end: 0.01
epsilon_start: 0.95
gamma: 0.95
lr: 0.1

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projects/codes/Sarsa/Train_CliffWalking-v0_Sarsa_20221030-021146/logs/log.txt Normal file
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2022-10-30 02:11:46 - r - INFO: - n_states: 48, n_actions: 4
2022-10-30 02:11:46 - r - INFO: - Start training!
2022-10-30 02:11:46 - r - INFO: - Env: CliffWalking-v0, Algorithm: Sarsa, Device: cpu
2022-10-30 02:11:46 - r - INFO: - Episode: 1/800, Reward: -1091.00, Steps:200, Epislon: 0.491
2022-10-30 02:11:46 - r - INFO: - Episode: 2/800, Reward: -320.00, Steps:122, Epislon: 0.329
2022-10-30 02:11:46 - r - INFO: - Episode: 3/800, Reward: -794.00, Steps:200, Epislon: 0.173
2022-10-30 02:11:46 - r - INFO: - Episode: 4/800, Reward: -596.00, Steps:200, Epislon: 0.094
2022-10-30 02:11:46 - r - INFO: - Episode: 5/800, Reward: -398.00, Steps:200, Epislon: 0.053
2022-10-30 02:11:46 - r - INFO: - Episode: 6/800, Reward: -59.00, Steps:59, Epislon: 0.045
2022-10-30 02:11:46 - r - INFO: - Episode: 7/800, Reward: -299.00, Steps:200, Epislon: 0.028
2022-10-30 02:11:46 - r - INFO: - Episode: 8/800, Reward: -82.00, Steps:82, Epislon: 0.024
2022-10-30 02:11:46 - r - INFO: - Episode: 9/800, Reward: -125.00, Steps:125, Epislon: 0.019
2022-10-30 02:11:46 - r - INFO: - Episode: 10/800, Reward: -75.00, Steps:75, Epislon: 0.017
2022-10-30 02:11:46 - r - INFO: - Episode: 11/800, Reward: -285.00, Steps:186, Epislon: 0.014
2022-10-30 02:11:46 - r - INFO: - Episode: 12/800, Reward: -103.00, Steps:103, Epislon: 0.013
2022-10-30 02:11:46 - r - INFO: - Episode: 13/800, Reward: -103.00, Steps:103, Epislon: 0.012
2022-10-30 02:11:46 - r - INFO: - Episode: 14/800, Reward: -131.00, Steps:131, Epislon: 0.011
2022-10-30 02:11:46 - r - INFO: - Episode: 15/800, Reward: -53.00, Steps:53, Epislon: 0.011
2022-10-30 02:11:46 - r - INFO: - Episode: 16/800, Reward: -113.00, Steps:113, Epislon: 0.011
2022-10-30 02:11:46 - r - INFO: - Episode: 17/800, Reward: -125.00, Steps:125, Epislon: 0.010
2022-10-30 02:11:46 - r - INFO: - Episode: 18/800, Reward: -95.00, Steps:95, Epislon: 0.010
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2022-10-30 02:11:46 - r - INFO: - Episode: 27/800, Reward: -97.00, Steps:97, Epislon: 0.010
2022-10-30 02:11:46 - r - INFO: - Episode: 28/800, Reward: -206.00, Steps:107, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 108/800, Reward: -49.00, Steps:49, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 109/800, Reward: -65.00, Steps:65, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 110/800, Reward: -45.00, Steps:45, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 111/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 112/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 113/800, Reward: -51.00, Steps:51, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 114/800, Reward: -43.00, Steps:43, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 115/800, Reward: -47.00, Steps:47, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 116/800, Reward: -41.00, Steps:41, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 117/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 118/800, Reward: -31.00, Steps:31, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 119/800, Reward: -180.00, Steps:81, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 120/800, Reward: -43.00, Steps:43, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 121/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 122/800, Reward: -47.00, Steps:47, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 123/800, Reward: -65.00, Steps:65, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 124/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 125/800, Reward: -31.00, Steps:31, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 126/800, Reward: -49.00, Steps:49, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 127/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 128/800, Reward: -45.00, Steps:45, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 129/800, Reward: -49.00, Steps:49, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 130/800, Reward: -37.00, Steps:37, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 131/800, Reward: -49.00, Steps:49, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 132/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 133/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 134/800, Reward: -35.00, Steps:35, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 135/800, Reward: -37.00, Steps:37, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 136/800, Reward: -43.00, Steps:43, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 137/800, Reward: -31.00, Steps:31, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 138/800, Reward: -51.00, Steps:51, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 139/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 140/800, Reward: -51.00, Steps:51, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 141/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 142/800, Reward: -35.00, Steps:35, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 143/800, Reward: -31.00, Steps:31, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 144/800, Reward: -41.00, Steps:41, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 145/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 146/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 147/800, Reward: -47.00, Steps:47, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 148/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 149/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 150/800, Reward: -45.00, Steps:45, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 151/800, Reward: -31.00, Steps:31, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 152/800, Reward: -33.00, Steps:33, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 153/800, Reward: -31.00, Steps:31, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 154/800, Reward: -148.00, Steps:49, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 155/800, Reward: -41.00, Steps:41, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 156/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 157/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 158/800, Reward: -31.00, Steps:31, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 159/800, Reward: -33.00, Steps:33, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 160/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 161/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 162/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 163/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 164/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 165/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 166/800, Reward: -35.00, Steps:35, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 167/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 168/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 169/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 170/800, Reward: -41.00, Steps:41, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 171/800, Reward: -39.00, Steps:39, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 172/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 173/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 174/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 175/800, Reward: -31.00, Steps:31, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 176/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 177/800, Reward: -155.00, Steps:56, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 178/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 179/800, Reward: -37.00, Steps:37, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 180/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 181/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 182/800, Reward: -39.00, Steps:39, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 183/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 184/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 185/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 186/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 187/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 188/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 189/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 190/800, Reward: -42.00, Steps:42, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 191/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 192/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 193/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 194/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 195/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 196/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 197/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 198/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 199/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 200/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 201/800, Reward: -33.00, Steps:33, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 202/800, Reward: -37.00, Steps:37, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 203/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 204/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 205/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 206/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 207/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 208/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 209/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 210/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 211/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 212/800, Reward: -37.00, Steps:37, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 213/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 214/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 215/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 216/800, Reward: -31.00, Steps:31, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 217/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 218/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 219/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 220/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 221/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 222/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 223/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 224/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 225/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 226/800, Reward: -43.00, Steps:43, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 227/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 228/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 229/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 230/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 231/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 232/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 233/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 234/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 235/800, Reward: -31.00, Steps:31, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 236/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 237/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 238/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 239/800, Reward: -30.00, Steps:30, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 240/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 241/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 242/800, Reward: -24.00, Steps:24, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 243/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 244/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 245/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 246/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 247/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 248/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 249/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 250/800, Reward: -29.00, Steps:29, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 251/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 252/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 253/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 254/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 255/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 256/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 257/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 258/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 259/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 260/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 261/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 262/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 263/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 264/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 265/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 266/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 267/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 268/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 269/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 270/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 271/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 272/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 273/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 274/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 275/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 276/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 277/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 278/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 279/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 280/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 281/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 282/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 283/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 284/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 285/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 286/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 287/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 288/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 289/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 290/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 291/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 292/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 293/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 294/800, Reward: -120.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 295/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 296/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 297/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 298/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 299/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 300/800, Reward: -35.00, Steps:35, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 301/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 302/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 303/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 304/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 305/800, Reward: -23.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 306/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 307/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 308/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 309/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 310/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 311/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 312/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 313/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 314/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 315/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 316/800, Reward: -32.00, Steps:32, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 317/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 318/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 319/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 320/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 321/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 322/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 323/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 324/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 325/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 326/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 327/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 328/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 329/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 330/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 331/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 332/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 333/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 334/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 335/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 336/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 337/800, Reward: -26.00, Steps:26, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 338/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 339/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 340/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 341/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 342/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 343/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 344/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 345/800, Reward: -27.00, Steps:27, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 346/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 347/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 348/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 349/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 350/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 351/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 352/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 353/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 354/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 355/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 356/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 357/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 358/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 359/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 360/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 361/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 362/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 363/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 364/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 365/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 366/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 367/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 368/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 369/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 370/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 371/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 372/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 373/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 374/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 375/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 376/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 377/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 378/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 379/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 380/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 381/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 382/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 383/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 384/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 385/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 386/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 387/800, Reward: -25.00, Steps:25, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 388/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 389/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 390/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 391/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 392/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 393/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 394/800, Reward: -122.00, Steps:23, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 395/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 396/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 397/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 398/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 399/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 400/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 401/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 402/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 403/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 404/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 405/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 406/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 407/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 408/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 409/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 410/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 411/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 412/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 413/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 414/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 415/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 416/800, Reward: -17.00, Steps:17, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 418/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 419/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 420/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 421/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 422/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 423/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 424/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 425/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 426/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 427/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 428/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 429/800, Reward: -17.00, Steps:17, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 432/800, Reward: -15.00, Steps:15, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 434/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 435/800, Reward: -21.00, Steps:21, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 437/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 438/800, Reward: -17.00, Steps:17, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 453/800, Reward: -15.00, Steps:15, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 459/800, Reward: -15.00, Steps:15, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 463/800, Reward: -15.00, Steps:15, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 472/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 473/800, Reward: -21.00, Steps:21, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 475/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 476/800, Reward: -15.00, Steps:15, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 478/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 479/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 480/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 481/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 482/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 483/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 484/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 485/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 486/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 487/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 488/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 489/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 490/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 491/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 492/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 493/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 494/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 495/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 496/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 497/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 498/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 499/800, Reward: -15.00, Steps:15, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 501/800, Reward: -15.00, Steps:15, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 506/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 507/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 508/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 509/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 510/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 511/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 512/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 513/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 514/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 515/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 516/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 517/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 518/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 519/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 520/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 521/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 522/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 523/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 524/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 525/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 526/800, Reward: -15.00, Steps:15, Epislon: 0.010
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2022-10-30 02:11:47 - r - INFO: - Episode: 528/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 529/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 530/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 531/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 532/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 533/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 534/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 535/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 536/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 537/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 538/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 539/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 540/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 541/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 542/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 543/800, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 544/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 545/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 546/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 547/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 548/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 549/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 550/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 551/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 552/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 553/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 554/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 555/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 556/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 557/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 558/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:47 - r - INFO: - Episode: 559/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 560/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 561/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 562/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 563/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 564/800, Reward: -20.00, Steps:20, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 565/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 566/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 567/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 568/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 569/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 570/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 571/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 572/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 573/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 574/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 575/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 576/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 577/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 578/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 579/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 580/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 581/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 582/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 583/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 584/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 585/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 586/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 587/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 588/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 589/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 590/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 591/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 592/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 593/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 594/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 595/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 596/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 597/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 598/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 599/800, Reward: -16.00, Steps:16, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 600/800, Reward: -16.00, Steps:16, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 601/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 602/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 603/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 604/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 605/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 606/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 607/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 608/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 609/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 610/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 611/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 612/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 613/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 614/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 615/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 616/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 617/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 618/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 619/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 620/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 621/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 622/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 623/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 624/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 625/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 626/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 627/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 628/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 629/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 630/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 631/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 632/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 633/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 634/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 635/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 636/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 637/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 638/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 639/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 640/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 641/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 642/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 643/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 644/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 645/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 646/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 647/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 648/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 649/800, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 650/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 651/800, Reward: -15.00, Steps:15, Epislon: 0.010
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2022-10-30 02:11:48 - r - INFO: - Episode: 653/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 654/800, Reward: -17.00, Steps:17, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 655/800, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:11:48 - r - INFO: - Episode: 656/800, Reward: -15.00, Steps:15, Epislon: 0.010
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2022-10-30 02:11:48 - r - INFO: - Finish training!

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1 episodes rewards steps
2 0 -1091 200
3 1 -320 122
4 2 -794 200
5 3 -596 200
6 4 -398 200
7 5 -59 59
8 6 -299 200
9 7 -82 82
10 8 -125 125
11 9 -75 75
12 10 -285 186
13 11 -103 103
14 12 -103 103
15 13 -131 131
16 14 -53 53
17 15 -113 113
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19 17 -95 95
20 18 -97 97
21 19 -145 145
22 20 -89 89
23 21 -97 97
24 22 -115 115
25 23 -121 121
26 24 -53 53
27 25 -111 111
28 26 -97 97
29 27 -206 107
30 28 -147 147
31 29 -36 36
32 30 -216 117
33 31 -103 103
34 32 -87 87
35 33 -80 80
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38 36 -143 44
39 37 -241 142
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projects/codes/Sarsa/Train_Racetrack-v0_Sarsa_20221030-021315/config.yaml Normal file
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general_cfg:
algo_name: Sarsa
device: cpu
env_name: Racetrack-v0
load_checkpoint: false
load_path: Train_CartPole-v1_DQN_20221026-054757
max_steps: 200
mode: train
save_fig: true
seed: 10
show_fig: false
test_eps: 20
train_eps: 400
algo_cfg:
epsilon_decay: 200
epsilon_end: 0.01
epsilon_start: 0.9
gamma: 0.99
lr: 0.1

404
projects/codes/Sarsa/Train_Racetrack-v0_Sarsa_20221030-021315/logs/log.txt Normal file
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2022-10-30 02:13:15 - r - INFO: - n_states: 4, n_actions: 9
2022-10-30 02:13:15 - r - INFO: - Start training!
2022-10-30 02:13:15 - r - INFO: - Env: Racetrack-v0, Algorithm: Sarsa, Device: cpu
2022-10-30 02:13:15 - r - INFO: - Episode: 1/400, Reward: -870.00, Steps:200, Epislon: 0.336
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2022-10-30 02:13:21 - r - INFO: - Episode: 322/400, Reward: 4.00, Steps:6, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 323/400, Reward: -16.00, Steps:16, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 324/400, Reward: 4.00, Steps:6, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 325/400, Reward: -18.00, Steps:18, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 326/400, Reward: -36.00, Steps:26, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 327/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 328/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 329/400, Reward: -28.00, Steps:18, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 330/400, Reward: -31.00, Steps:21, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 331/400, Reward: -1.00, Steps:11, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 332/400, Reward: -109.00, Steps:59, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 333/400, Reward: -29.00, Steps:19, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 334/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 335/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 336/400, Reward: 0.00, Steps:10, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 337/400, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 338/400, Reward: -12.00, Steps:12, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 339/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 340/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 341/400, Reward: -14.00, Steps:14, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 342/400, Reward: -35.00, Steps:25, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 343/400, Reward: -16.00, Steps:16, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 344/400, Reward: -21.00, Steps:21, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 345/400, Reward: -28.00, Steps:18, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 346/400, Reward: 2.00, Steps:8, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 347/400, Reward: -12.00, Steps:12, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 348/400, Reward: -28.00, Steps:18, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 349/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 350/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 351/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 352/400, Reward: -10.00, Steps:10, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 353/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 354/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 355/400, Reward: -62.00, Steps:32, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 356/400, Reward: 5.00, Steps:5, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 357/400, Reward: 4.00, Steps:6, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 358/400, Reward: -28.00, Steps:18, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 359/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 360/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 361/400, Reward: 2.00, Steps:8, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 362/400, Reward: 2.00, Steps:8, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 363/400, Reward: -16.00, Steps:16, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 364/400, Reward: 2.00, Steps:8, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 365/400, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 366/400, Reward: -18.00, Steps:18, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 367/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 368/400, Reward: -18.00, Steps:18, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 369/400, Reward: -15.00, Steps:15, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 370/400, Reward: 5.00, Steps:5, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 371/400, Reward: -29.00, Steps:19, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 372/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 373/400, Reward: -14.00, Steps:14, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 374/400, Reward: 1.00, Steps:9, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 375/400, Reward: -19.00, Steps:19, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 376/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 377/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 378/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 379/400, Reward: -31.00, Steps:21, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 380/400, Reward: 2.00, Steps:8, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 381/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 382/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 383/400, Reward: -14.00, Steps:14, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 384/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 385/400, Reward: 2.00, Steps:8, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 386/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 387/400, Reward: 4.00, Steps:6, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 388/400, Reward: -8.00, Steps:8, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 389/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 390/400, Reward: 4.00, Steps:6, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 391/400, Reward: -13.00, Steps:13, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 392/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 393/400, Reward: -12.00, Steps:12, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 394/400, Reward: -32.00, Steps:22, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 395/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 396/400, Reward: -27.00, Steps:17, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 397/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 398/400, Reward: 3.00, Steps:7, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 399/400, Reward: -37.00, Steps:27, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Episode: 400/400, Reward: -57.00, Steps:37, Epislon: 0.010
2022-10-30 02:13:21 - r - INFO: - Finish training!

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19
projects/codes/Sarsa/config/CliffWalking-v0_Sarsa_Test.yaml Normal file
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general_cfg:
algo_name: Sarsa
device: cpu
env_name: CliffWalking-v0
mode: test
load_checkpoint: true
load_path: Train_CliffWalking-v0_Sarsa_20221030-021146
max_steps: 200
save_fig: true
seed: 1
show_fig: false
test_eps: 20
train_eps: 400
algo_cfg:
epsilon_decay: 300
epsilon_end: 0.01
epsilon_start: 0.95
gamma: 0.95
lr: 0.1

19
projects/codes/Sarsa/config/CliffWalking-v0_Sarsa_Train.yaml Normal file
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general_cfg:
algo_name: Sarsa
device: cpu
env_name: CliffWalking-v0
mode: train
load_checkpoint: false
load_path: Train_CartPole-v1_DQN_20221026-054757
max_steps: 200
save_fig: true
seed: 1
show_fig: false
test_eps: 20
train_eps: 800
algo_cfg:
epsilon_decay: 300
epsilon_end: 0.01
epsilon_start: 0.95
gamma: 0.95
lr: 0.1

19
projects/codes/Sarsa/config/Racetrack-v0_Sarsa_Test.yaml Normal file
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general_cfg:
algo_name: Sarsa
device: cpu
env_name: Racetrack-v0
mode: test
load_checkpoint: true
load_path: Train_Racetrack-v0_Sarsa_20221030-021315
max_steps: 200
save_fig: true
seed: 10
show_fig: false
test_eps: 20
train_eps: 400
algo_cfg:
epsilon_decay: 200
epsilon_end: 0.01
epsilon_start: 0.9
gamma: 0.99
lr: 0.1

19
projects/codes/Sarsa/config/Racetrack-v0_Sarsa_Train.yaml Normal file
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general_cfg:
algo_name: Sarsa
device: cpu
env_name: Racetrack-v0
mode: train
load_checkpoint: false
load_path: Train_CartPole-v1_DQN_20221026-054757
max_steps: 200
save_fig: true
seed: 10
show_fig: false
test_eps: 20
train_eps: 400
algo_cfg:
epsilon_decay: 200
epsilon_end: 0.01
epsilon_start: 0.9
gamma: 0.99
lr: 0.1

35
projects/codes/Sarsa/config/config.py Normal file
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#!/usr/bin/env python
# coding=utf-8
'''
Author: JiangJi
Email: johnjim0816@gmail.com
Date: 2022-10-30 01:23:07
LastEditor: JiangJi
LastEditTime: 2022-10-30 02:01:54
Discription: default parameters of QLearning
'''
from common.config import GeneralConfig,AlgoConfig
class GeneralConfigSarsa(GeneralConfig):
def __init__(self) -> None:
self.env_name = "CliffWalking-v0" # name of environment
self.algo_name = "Sarsa" # name of algorithm
self.mode = "train" # train or test
self.seed = 1 # random seed
self.device = "cpu" # device to use
self.train_eps = 400 # number of episodes for training
self.test_eps = 20 # number of episodes for testing
self.max_steps = 200 # max steps for each episode
self.load_checkpoint = False
self.load_path = "tasks" # path to load model
self.show_fig = False # show figure or not
self.save_fig = True # save figure or not
class AlgoConfigSarsa(AlgoConfig):
def __init__(self) -> None:
# set epsilon_start=epsilon_end can obtain fixed epsilon=epsilon_end
self.epsilon_start = 0.95 # epsilon start value
self.epsilon_end = 0.01 # epsilon end value
self.epsilon_decay = 300 # epsilon decay rate
self.gamma = 0.90 # discount factor
self.lr = 0.1 # learning rate

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projects/codes/Sarsa/main.py
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#!/usr/bin/env python
# coding=utf-8
'''
Author: John
Email: johnjim0816@gmail.com
Date: 2021-03-11 17:59:16
LastEditor: John
LastEditTime: 2022-08-26 23:03:39
Discription:
Environment:
'''
import sys,os
os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE" # avoid "OMP: Error #15: Initializing libiomp5md.dll, but found libiomp5md.dll already initialized."
curr_path = os.path.dirname(os.path.abspath(__file__)) # current path
parent_path = os.path.dirname(curr_path) # parent path
sys.path.append(parent_path) # add path to system path
import gym
import datetime
import argparse
from envs.register import register_env
from envs.wrappers import CliffWalkingWapper
from Sarsa.sarsa import Sarsa
from common.utils import all_seed
from common.launcher import Launcher
class Main(Launcher):
def get_args(self):
curr_time = datetime.datetime.now().strftime("%Y%m%d-%H%M%S") # obtain current time
parser = argparse.ArgumentParser(description="hyperparameters")
parser.add_argument('--algo_name',default = 'Sarsa',type=str,help="name of algorithm")
parser.add_argument('--env_name',default = 'Racetrack-v0',type=str,help="name of environment")
parser.add_argument('--train_eps',default = 300,type=int,help="episodes of training")
parser.add_argument('--test_eps',default = 20,type=int,help="episodes of testing")
parser.add_argument('--ep_max_steps',default = 100000,type=int,help="steps per episode, much larger value can simulate infinite steps")
parser.add_argument('--gamma',default=0.99,type=float,help="discounted factor")
parser.add_argument('--epsilon_start',default=0.90,type=float,help="initial value of epsilon")
parser.add_argument('--epsilon_end',default=0.01,type=float,help="final value of epsilon")
parser.add_argument('--epsilon_decay',default=200,type=int,help="decay rate of epsilon")
parser.add_argument('--lr',default=0.2,type=float,help="learning rate")
parser.add_argument('--device',default='cpu',type=str,help="cpu or cuda")
parser.add_argument('--seed',default=10,type=int,help="seed")
parser.add_argument('--show_fig',default=False,type=bool,help="if show figure or not")
parser.add_argument('--save_fig',default=True,type=bool,help="if save figure or not")
args = parser.parse_args()
default_args = {'result_path':f"{curr_path}/outputs/{args.env_name}/{curr_time}/results/",
'model_path':f"{curr_path}/outputs/{args.env_name}/{curr_time}/models/",
}
args = {**vars(args),**default_args} # type(dict)
return args
def env_agent_config(self,cfg):
register_env(cfg['env_name'])
env = gym.make(cfg['env_name'])
if cfg['seed'] !=0: # set random seed
all_seed(env,seed= cfg['seed'])
if cfg['env_name'] == 'CliffWalking-v0':
env = CliffWalkingWapper(env)
try: # state dimension
n_states = env.observation_space.n # print(hasattr(env.observation_space, 'n'))
except AttributeError:
n_states = env.observation_space.shape[0] # print(hasattr(env.observation_space, 'shape'))
n_actions = env.action_space.n # action dimension
print(f"n_states: {n_states}, n_actions: {n_actions}")
cfg.update({"n_states":n_states,"n_actions":n_actions}) # update to cfg paramters
agent = Sarsa(cfg)
return env,agent
def train(self,cfg,env,agent):
print("Start training!")
print(f"Env: {cfg['env_name']}, Algorithm: {cfg['algo_name']}, Device: {cfg['device']}")
rewards = [] # record rewards for all episodes
steps = [] # record steps for all episodes
for i_ep in range(cfg['train_eps']):
ep_reward = 0 # reward per episode
ep_step = 0 # step per episode
state = env.reset() # reset and obtain initial state
action = agent.sample_action(state)
# while True:
for _ in range(cfg['ep_max_steps']):
next_state, reward, done, _ = env.step(action) # update env and return transitions
next_action = agent.sample_action(next_state)
agent.update(state, action, reward, next_state, next_action,done) # update agent
state = next_state # update state
action = next_action
ep_reward += reward
ep_step += 1
if done:
break
rewards.append(ep_reward)
steps.append(ep_step)
if (i_ep+1)%10==0:
print(f'Episode: {i_ep+1}/{cfg["train_eps"]}, Reward: {ep_reward:.2f}, Steps: {ep_step}, Epislon: {agent.epsilon:.3f}')
print("Finish training!")
return {'episodes':range(len(rewards)),'rewards':rewards,'steps':steps}
def test(self,cfg,env,agent):
print("Start testing!")
print(f"Env: {cfg['env_name']}, Algorithm: {cfg['algo_name']}, Device: {cfg['device']}")
rewards = [] # record rewards for all episodes
steps = [] # record steps for all episodes
for i_ep in range(cfg['test_eps']):
ep_reward = 0 # reward per episode
ep_step = 0
state = env.reset() # reset and obtain initial state
for _ in range(cfg['ep_max_steps']):
action = agent.predict_action(state)
next_state, reward, done, _ = env.step(action)
state = next_state
ep_reward+=reward
ep_step+=1
if done:
break
rewards.append(ep_reward)
steps.append(ep_step)
print(f"Episode: {i_ep+1}/{cfg['test_eps']}, Steps: {ep_step}, Reward: {ep_reward:.2f}")
print("Finish testing!")
return {'episodes':range(len(rewards)),'rewards':rewards,'steps':steps}
if __name__ == "__main__":
main = Main()
main.run()

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projects/codes/Sarsa/outputs/CliffWalking-v0/20220825-213316/results/params.json
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{
"algo_name": "Sarsa",
"env_name": "CliffWalking-v0",
"train_eps": 400,
"test_eps": 20,
"gamma": 0.9,
"epsilon_start": 0.95,
"epsilon_end": 0.01,
"epsilon_decay": 300,
"lr": 0.1,
"device": "cpu",
"seed": 10,
"show_fig": false,
"save_fig": true,
"result_path": "/Users/jj/Desktop/rl-tutorials/codes/Sarsa/outputs/CliffWalking-v0/20220825-213316/results/",
"model_path": "/Users/jj/Desktop/rl-tutorials/codes/Sarsa/outputs/CliffWalking-v0/20220825-213316/models/",
"n_states": 48,
"n_actions": 4
}

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401
projects/codes/Sarsa/outputs/CliffWalking-v0/20220825-213316/results/training_results.csv
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{"algo_name": "Sarsa", "env_name": "Racetrack-v0", "train_eps": 300, "test_eps": 20, "gamma": 0.99, "epsilon_start": 0.9, "epsilon_end": 0.01, "epsilon_decay": 200, "lr": 0.2, "device": "cpu", "seed": 10, "show_fig": false, "save_fig": true, "result_path": "/Users/jj/Desktop/rl-tutorials/codes/Sarsa/outputs/Racetrack-v0/20220825-212738/results/", "model_path": "/Users/jj/Desktop/rl-tutorials/codes/Sarsa/outputs/Racetrack-v0/20220825-212738/models/", "n_states": 4, "n_actions": 9}

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16
projects/codes/Sarsa/sarsa.py
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@@ -5,7 +5,7 @@ Author: John
Email: johnjim0816@gmail.com
Date: 2021-03-12 16:58:16
LastEditor: John
LastEditTime: 2022-08-25 21:26:08
LastEditTime: 2022-10-30 02:00:51
Discription:
Environment:
'''
@@ -15,14 +15,14 @@ import torch
import math
class Sarsa(object):
def __init__(self,cfg):
self.n_actions = cfg['n_actions']
self.lr = cfg['lr']
self.gamma = cfg['gamma']
self.epsilon = cfg['epsilon_start']
self.n_actions = cfg.n_actions
self.lr = cfg.lr
self.gamma = cfg.gamma
self.epsilon = cfg.epsilon_start
self.sample_count = 0
self.epsilon_start = cfg['epsilon_start']
self.epsilon_end = cfg['epsilon_end']
self.epsilon_decay = cfg['epsilon_decay']
self.epsilon_start = cfg.epsilon_start
self.epsilon_end = cfg.epsilon_end
self.epsilon_decay = cfg.epsilon_decay
self.Q_table = defaultdict(lambda: np.zeros(self.n_actions)) # Q table
def sample_action(self, state):
''' another way to represent e-greedy policy

106
projects/codes/Sarsa/task0.py Normal file
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@@ -0,0 +1,106 @@
#!/usr/bin/env python
# coding=utf-8
'''
Author: JiangJi
Email: johnjim0816@gmail.com
Date: 2022-09-19 14:48:16
LastEditor: JiangJi
LastEditTime: 2022-10-30 02:11:31
Discription:
'''
import sys,os
os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE" # avoid "OMP: Error #15: Initializing libiomp5md.dll, but found libiomp5md.dll already initialized."
curr_path = os.path.dirname(os.path.abspath(__file__)) # current path
parent_path = os.path.dirname(curr_path) # parent path
sys.path.append(parent_path) # add path to system path
import gym
import datetime
import argparse
from envs.register import register_env
from envs.wrappers import CliffWalkingWapper
from Sarsa.sarsa import Sarsa
from common.utils import all_seed,merge_class_attrs
from common.launcher import Launcher
from config.config import GeneralConfigSarsa,AlgoConfigSarsa
class Main(Launcher):
def __init__(self) -> None:
super().__init__()
self.cfgs['general_cfg'] = merge_class_attrs(self.cfgs['general_cfg'],GeneralConfigSarsa())
self.cfgs['algo_cfg'] = merge_class_attrs(self.cfgs['algo_cfg'],AlgoConfigSarsa())
def env_agent_config(self,cfg,logger):
register_env(cfg.env_name)
env = gym.make(cfg.env_name,new_step_api=False) # create env
if cfg.env_name == 'CliffWalking-v0':
env = CliffWalkingWapper(env)
if cfg.seed !=0: # set random seed
all_seed(env,seed=cfg.seed)
try: # state dimension
n_states = env.observation_space.n # print(hasattr(env.observation_space, 'n'))
except AttributeError:
n_states = env.observation_space.shape[0] # print(hasattr(env.observation_space, 'shape'))
n_actions = env.action_space.n # action dimension
logger.info(f"n_states: {n_states}, n_actions: {n_actions}") # print info
# update to cfg paramters
setattr(cfg, 'n_states', n_states)
setattr(cfg, 'n_actions', n_actions)
agent = Sarsa(cfg)
return env,agent
def train(self,cfg,env,agent,logger):
logger.info("Start training!")
logger.info(f"Env: {cfg.env_name}, Algorithm: {cfg.algo_name}, Device: {cfg.device}")
rewards = [] # record rewards for all episodes
steps = [] # record steps for all episodes
for i_ep in range(cfg.train_eps):
ep_reward = 0 # reward per episode
ep_step = 0 # step per episode
state = env.reset() # reset and obtain initial state
action = agent.sample_action(state)
# while True:
for _ in range(cfg.max_steps):
next_state, reward, done, _ = env.step(action) # update env and return transitions
next_action = agent.sample_action(next_state)
agent.update(state, action, reward, next_state, next_action,done) # update agent
state = next_state # update state
action = next_action
ep_reward += reward
ep_step += 1
if done:
break
rewards.append(ep_reward)
steps.append(ep_step)
logger.info(f'Episode: {i_ep+1}/{cfg.train_eps}, Reward: {ep_reward:.2f}, Steps:{ep_step:d}, Epislon: {agent.epsilon:.3f}')
logger.info("Finish training!")
return {'episodes':range(len(rewards)),'rewards':rewards,'steps':steps}
def test(self,cfg,env,agent,logger):
logger.info("Start testing!")
logger.info(f"Env: {cfg.env_name}, Algorithm: {cfg.algo_name}, Device: {cfg.device}")
rewards = [] # record rewards for all episodes
steps = [] # record steps for all episodes
for i_ep in range(cfg.test_eps):
ep_reward = 0 # reward per episode
ep_step = 0
state = env.reset() # reset and obtain initial state
for _ in range(cfg.max_steps):
action = agent.predict_action(state)
next_state, reward, done, _ = env.step(action)
state = next_state
ep_reward+=reward
ep_step+=1
if done:
break
rewards.append(ep_reward)
steps.append(ep_step)
logger.info(f"Episode: {i_ep+1}/{cfg.test_eps}, Reward: {ep_reward:.2f}, Steps:{ep_step:d}")
logger.info("Finish testing!")
return {'episodes':range(len(rewards)),'rewards':rewards,'steps':steps}
if __name__ == "__main__":
main = Main()
main.run()