Create config_ma2c_real.ini

real_net/ma2c/data/config_ma2c_real.ini

@@ -0,0 +1,49 @@
+[MODEL_CONFIG]
+rmsp_alpha = 0.99
+rmsp_epsilon = 1e-5
+max_grad_norm = 40
+gamma = 0.99
+lr_init = 5e-4
+lr_decay = constant
+entropy_coef_init = 0.01
+entropy_coef_min = 0.01
+entropy_decay = constant
+entropy_ratio = 0.5
+value_coef = 0.5
+num_fw = 128
+num_ft = 32
+num_lstm = 64
+num_fp = 64
+batch_size = 10
+reward_norm = 1.0
+reward_clip = 2.0
+
+[TRAIN_CONFIG]
+total_step = 2e6
+test_interval = 2e4
+log_interval = 1e4
+
+[ENV_CONFIG]
+clip_wave = 2.0
+clip_wait = 2.0
+; agent is greedy, iqll, iqld, ia2c, ma2c, a2c.
+agent = ma2c
+; coop discount is used to discount the neighbors' impact
+coop_gamma = 0.9
+data_path = ./real_net/data/
+price_data = ./real_net/price_data/
+; key = ^GSPC_2011
+; key = ^GSPC
+key = EURUSD_lastmonth
+window_size = 10
+balance = 10000
+; the normailization is based on typical values in sim
+norm_wave = 5.0
+norm_wait = 30.0
+coef_wait = 0
+; objective is chosen from queue, wait, hybrid
+objective = queue
+scenario = real_net
+seed = 42
+test_seeds = 10000,20000,30000
+yellow_interval_sec = 2