Nguyen Viet Tuan
47 lines
958 B
INI
47 lines
958 B
INI
[MODEL_CONFIG]
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rmsp_alpha = 0.99
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rmsp_epsilon = 1e-5
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max_grad_norm = 40
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gamma = 0.99
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lr_init = 5e-4
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lr_decay = constant
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entropy_coef_init = 0.01
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entropy_coef_min = 0.01
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entropy_decay = constant
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entropy_ratio = 0.5
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value_coef = 0.5
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num_fw = 128
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num_ft = 32
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num_lstm = 64
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num_fp = 64
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batch_size = 10
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reward_norm = 1.0
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reward_clip = 2.0
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[TRAIN_CONFIG]
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total_step = 2e6
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test_interval = 2e4
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log_interval = 1e4
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[ENV_CONFIG]
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clip_wave = 2.0
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clip_wait = 2.0
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; agent is greedy, iqll, iqld, ia2c, ma2c, a2c.
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agent = ma2c
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; coop discount is used to discount the neighbors' impact
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coop_gamma = 0.9
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data_path = ./real_net/data/
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price_data = ./real_net/price_data/
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key = EURUSD_lastmonth
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window_size = 10
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balance = 995
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; the normailization is based on typical values in sim
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norm_wave = 5.0
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norm_wait = 30.0
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coef_wait = 0
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; objective is chosen from queue, wait, hybrid
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objective = queue
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scenario = real_net
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seed = 42
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test_seeds = 10000,20000,30000
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yellow_interval_sec = 2 |