LunarLander-v2 - DQN - Agent

DQN-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f6b64dc88b5e0380f5f6ca214affd12c8192858045ce157b061812acd76391bb
-size 106654
+oid sha256:c2b84ee34ac58d46edcaf9ea22fb24ceb85f0950103879c715ee3bf1db939ff0
+size 106659

DQN-LunarLander-v2/data

@@ -5,15 +5,15 @@
         "__module__": "stable_baselines3.dqn.policies",
         "__annotations__": "{'q_net': <class 'stable_baselines3.dqn.policies.QNetwork'>, 'q_net_target': <class 'stable_baselines3.dqn.policies.QNetwork'>}",
         "__doc__": "\n    Policy class with Q-Value Net and target net for DQN\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ",
-        "__init__": "<function DQNPolicy.__init__ at 0x7ed0e49f2830>",
-        "_build": "<function DQNPolicy._build at 0x7ed0e49f28c0>",
-        "make_q_net": "<function DQNPolicy.make_q_net at 0x7ed0e49f2950>",
-        "forward": "<function DQNPolicy.forward at 0x7ed0e49f29e0>",
-        "_predict": "<function DQNPolicy._predict at 0x7ed0e49f2a70>",
-        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7ed0e49f2b00>",
-        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7ed0e49f2b90>",
+        "__init__": "<function DQNPolicy.__init__ at 0x7e53234fa5f0>",
+        "_build": "<function DQNPolicy._build at 0x7e53234fa680>",
+        "make_q_net": "<function DQNPolicy.make_q_net at 0x7e53234fa710>",
+        "forward": "<function DQNPolicy.forward at 0x7e53234fa7a0>",
+        "_predict": "<function DQNPolicy._predict at 0x7e53234fa830>",
+        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7e53234fa8c0>",
+        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7e53234fa950>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7ed0e4a09440>"
+        "_abc_impl": "<_abc._abc_data object at 0x7e5323511640>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -22,12 +22,12 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1691082855347515290,
+    "start_time": 1691085597579096751,
     "learning_rate": 0.0001,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -35,16 +35,16 @@
     },
     "_last_original_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
-    "_episode_num": 2276,
+    "_episode_num": 2984,
     "use_sde": false,
     "sde_sample_freq": -1,
     "_current_progress_remaining": 0.0,
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
@@ -68,7 +68,7 @@
     },
     "action_space": {
         ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
-        ":serialized:": "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",
+        ":serialized:": "gAWVgQEAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlIwUbnVtcHkucmFuZG9tLl9waWNrbGWUjBBfX2dlbmVyYXRvcl9jdG9ylJOUjAVQQ0c2NJSFlFKUfZQojA1iaXRfZ2VuZXJhdG9ylIwFUENHNjSUjAVzdGF0ZZR9lChoI4oRgf4TtPXA4EXmkUhwNJPG/ACMA2luY5SKEEc8vl7FVPuAB1kbRIiC6k11jApoYXNfdWludDMylEsAjAh1aW50ZWdlcpRKg6dMcnVidWIu",
         "n": "4",
         "start": "0",
         "_shape": [],
@@ -88,12 +88,12 @@
         ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
         "__module__": "stable_baselines3.common.buffers",
         "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
-        "__init__": "<function ReplayBuffer.__init__ at 0x7ed0e49cecb0>",
-        "add": "<function ReplayBuffer.add at 0x7ed0e49ced40>",
-        "sample": "<function ReplayBuffer.sample at 0x7ed0e49cedd0>",
-        "_get_samples": "<function ReplayBuffer._get_samples at 0x7ed0e49cee60>",
+        "__init__": "<function ReplayBuffer.__init__ at 0x7e53234daa70>",
+        "add": "<function ReplayBuffer.add at 0x7e53234dab00>",
+        "sample": "<function ReplayBuffer.sample at 0x7e53234dab90>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7e53234dac20>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7ed0e49d3000>"
+        "_abc_impl": "<_abc._abc_data object at 0x7e53234e32c0>"
     },
     "replay_buffer_kwargs": {},
     "train_freq": {
@@ -103,8 +103,8 @@
     "use_sde_at_warmup": false,
     "exploration_initial_eps": 1.0,
     "exploration_final_eps": 0.05,
-    "exploration_fraction": 0.1,
-    "target_update_interval": 62,
+    "exploration_fraction": 0.5,
+    "target_update_interval": 625,
     "_n_calls": 62500,
     "max_grad_norm": 10,
     "exploration_rate": 0.05,
@@ -116,6 +116,6 @@
     "batch_norm_stats_target": [],
     "exploration_schedule": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     }
 }

DQN-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:844f21408ef1443323544e3fad1a5524ba0bf155259f05fef27dd38e64a78e4d
+oid sha256:06474b49bc68cacdc35665cc331cfe94eb3fb0a90f1179086ad3d185342b0fa3
 size 44911

DQN-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:113c5bfec36f357683affec7d5fe712ae57abd4bc3d6d68064c43c0d847bd1d2
+oid sha256:5f9fc67dd7d4eea712e65088ebde7e3e007a4ff55aa8e85d1fb6b4a94fe363f9
 size 44033

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -81.30 +/- 90.74
+      value: 58.89 +/- 158.77
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
-{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__module__": "stable_baselines3.dqn.policies", "__annotations__": "{'q_net': <class 'stable_baselines3.dqn.policies.QNetwork'>, 'q_net_target': <class 'stable_baselines3.dqn.policies.QNetwork'>}", "__doc__": "\n    Policy class with Q-Value Net and target net for DQN\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ", "__init__": "<function DQNPolicy.__init__ at 0x7ed0e49f2830>", "_build": "<function DQNPolicy._build at 0x7ed0e49f28c0>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7ed0e49f2950>", "forward": "<function DQNPolicy.forward at 0x7ed0e49f29e0>", "_predict": "<function DQNPolicy._predict at 0x7ed0e49f2a70>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7ed0e49f2b00>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7ed0e49f2b90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ed0e4a09440>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1691082855347515290, "learning_rate": 0.0001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 2276, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVQwwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQEe6IznA6+6MAWyUTawCjAF0lEdAk1bsqjJuEXV9lChoBkfAYa8q/dqL0mgHTQECaAhHQJNYTdEb5uZ1fZQoaAZHQFmgqmCROlBoB026AmgIR0CTWIvGZNO/dX2UKGgGR8BahKmCROk+aAdNtAFoCEdAk1mnhOxja3V9lChoBkfAaCuNb1RLsmgHTQACaAhHQJNaqM85jpd1fZQoaAZHwFf/BbfP5YZoB03rAWgIR0CTW2q0+kgwdX2UKGgGR0Bd91J17pmmaAdNIQJoCEdAk114gA6uGXV9lChoBkfAZSfsLORkmWgHTYUBaAhHQJNfwMgEEDB1fZQoaAZHwFek2g3974VoB03fAWgIR0CTYE5LRKHxdX2UKGgGR8BN79NWU8msaAdNpQFoCEdAk2Ctc0Ltu3V9lChoBkfAXu4eJYT0x2gHTagBaAhHQJNgwX668QJ1fZQoaAZHwGZRuTA31jBoB00HAmgIR0CTYXDJEH+qdX2UKGgGR8Bjvwi3XqZ/aAdNyAFoCEdAk2Hkyk9EC3V9lChoBkfAYTYZ3LV4HGgHTaQBaAhHQJNjPPD50r91fZQoaAZHwFZOUhmoR7JoB01QAWgIR0CTZl8KohpydX2UKGgGR8BiujPUrkKeaAdNlwFoCEdAk2hCkj5bhXV9lChoBkfATZFV94NZvGgHTUsBaAhHQJNqBKe05U91fZQoaAZHwFvkRPoFFDxoB03PAWgIR0CTagNmlImPdX2UKGgGR8Bd3cSCe2/jaAdNvAFoCEdAk2z7/Ot4iXV9lChoBkfAW/pPva11GWgHTb0BaAhHQJNtP6O5rgx1fZQoaAZHwF/JmzByjpNoB03JAWgIR0CTc8MVDa4+dX2UKGgGR8BUm1IEr5IpaAdNmAFoCEdAk3Skmx+rl3V9lChoBkfAXo4XcgyM1mgHTcMBaAhHQJN2QNWluWN1fZQoaAZHwF7YcHnlnyxoB03QAWgIR0CTeqfnwG4adX2UKGgGR8Be2o//vOQhaAdNygFoCEdAk3tNgOSW7nV9lChoBkfAY+vOSGJvYWgHTe0BaAhHQJN7v9Q40dl1fZQoaAZHQGBRVejVQRBoB014AmgIR0CTfRRcNYr8dX2UKGgGR8BdSIK+i8FqaAdNbQFoCEdAk4MBradtmHV9lChoBkdAW/Z8WsRxtGgHTd4CaAhHQJODVo9LYf51fZQoaAZHQFg2L7oB7u5oB02SAmgIR0CThkgte2NOdX2UKGgGR0BWbFRceKbbaAdNVgJoCEdAk4dSG8EmpnV9lChoBkfAZDKmk30f5mgHTeYBaAhHQJOHskGA09B1fZQoaAZHQFjXP9UCJXRoB00fAmgIR0CTiIEuxrzodX2UKGgGR8BhFWNWEK3NaAdN1wFoCEdAk4ipq7Ack3V9lChoBkfAZ4gE/0NBnmgHTe8BaAhHQJOMNRgqmTF1fZQoaAZHwGRkE8A7xNJoB00IAmgIR0CTjRGQ0XP7dX2UKGgGR8BhEZ8hLXcyaAdNCQJoCEdAk5L0KZ2IPHV9lChoBkfAYz+ZssQNC2gHTQoCaAhHQJOTzcQAdXF1fZQoaAZHwGGunLRrrPdoB031AWgIR0CTlAcBltj1dX2UKGgGR8BaZhVZLZi/aAdNwwFoCEdAk5QUvXbudHV9lChoBkfAZlWhdMTN+2gHTfoBaAhHQJOXDNRm9QJ1fZQoaAZHwFKIM2m51/5oB01+AWgIR0CTmQA3kxREdX2UKGgGR8BeeLEk0JnhaAdN0wFoCEdAk5qEDQqqfnV9lChoBkfAWznqB3A2ymgHTXMBaAhHQJOa3tD2Jzl1fZQoaAZHwGttzUAksz5oB00uAmgIR0CTmy7IDHOsdX2UKGgGR8Bg7x1X/5tWaAdN2wFoCEdAk5tAT/Q0GnV9lChoBkfAWKZ/MGHHm2gHTZUBaAhHQJObow22oeh1fZQoaAZHwFFZn2IwdsBoB01lAWgIR0CTnhWsRxtIdX2UKGgGR8BXhfhESdvsaAdN2wFoCEdAk55i5qdpZnV9lChoBkdAYPBwBo24u2gHTeABaAhHQJOftSKm8/V1fZQoaAZHwF/12YfGMn9oB03WAmgIR0CToYh3qzJIdX2UKGgGR0BbA0YKpkwwaAdN5AFoCEdAk6SKOo5xR3V9lChoBkfAY3ikvboKUmgHTXMBaAhHQJOllDVpbll1fZQoaAZHwFy+dq+JxedoB02oAWgIR0CTqAJGvwEydX2UKGgGR8Bj9/OGCZndaAdNyAFoCEdAk6nb4rSVnnV9lChoBkdAXqp5OafBe2gHTdwBaAhHQJOp9lmOEM91fZQoaAZHwGHpJTVDrqtoB02HAWgIR0CTrCTBqKxcdX2UKGgGR8BWloH5aePJaAdNigFoCEdAk64Ea2nbZnV9lChoBkfAXPDEl3QlbGgHTZQBaAhHQJOwMHVwxWV1fZQoaAZHwFfkrylN1yNoB024AWgIR0CTse+s5n14dX2UKGgGR8BrFopF1B+naAdNywFoCEdAk7NaF/QSjHV9lChoBkfAUDORDCxeLWgHTYwBaAhHQJO0Cj8DSw51fZQoaAZHwFit7EHdGiJoB02UAWgIR0CTtCx+az/qdX2UKGgGR0BkaaVObiIdaAdNLAJoCEdAk7TJ+MIeHXV9lChoBkfAWMY+A3DNyGgHTesBaAhHQJO1APmPo3d1fZQoaAZHwFN9S6UaAFxoB01yAWgIR0CTtkVf/m1ZdX2UKGgGR8Bq4B6a9bosaAdNpAFoCEdAk7Z5yp71I3V9lChoBkfAVJyJAMUh3mgHTVUBaAhHQJO4EYJmdy11fZQoaAZHwFC3F+/gzgxoB03BAWgIR0CTu85XU6PsdX2UKGgGR8Bagglv60pmaAdNhgFoCEdAk74lh1DBuXV9lChoBkfAYEAscQyylmgHTZkBaAhHQJO+/ijtXxR1fZQoaAZHwGDqZ1V5rxloB02IAWgIR0CTv8jjJdSmdX2UKGgGR0BPSO/UONHZaAdN5wFoCEdAk8EeJcgQpXV9lChoBkfAYfb/ACW/rWgHTYYBaAhHQJPBKZVn27F1fZQoaAZHwFkaU3n6l+FoB01+AWgIR0CTwjmF8G9pdX2UKGgGR8BmO5RKpT/AaAdNogFoCEdAk8TYlUp/gHV9lChoBkfAW1aMAFPi1mgHTWwBaAhHQJPGC+oLofV1fZQoaAZHwGGB4Xwb2lFoB02oAWgIR0CTxws3hn8LdX2UKGgGR8BgLGBYmsvJaAdN0QFoCEdAk8h15Sm65HV9lChoBkfAZqc8ujASF2gHTX8BaAhHQJPJjlLeyiV1fZQoaAZHwGO5OE/SpitoB035AWgIR0CTylFbFCLNdX2UKGgGR8BhK/Y6GQCCaAdNHAJoCEdAk8t6OtGNJnV9lChoBkdAYNInCwbEP2gHTUkCaAhHQJPPGN96Tnt1fZQoaAZHwFeOG3nZCfJoB02lAWgIR0CTz94Vh1DCdX2UKGgGR8BS0+2/i5uqaAdNTwFoCEdAk9EGUfPom3V9lChoBkfAWhaPZIxxk2gHTZcBaAhHQJPRqoP07Kd1fZQoaAZHwEvAUILPUrloB01dAWgIR0CT0br4FiazdX2UKGgGR8BkH7XJ5mh/aAdNiAFoCEdAk9HKdMCcPXV9lChoBkfAXbDQnhKlHmgHTYUBaAhHQJPSSLrHEMt1fZQoaAZHwFqp3yZrpJRoB01PAWgIR0CT1MxmkFfRdX2UKGgGR8Bkefacqe9SaAdNoQFoCEdAk9WyS7oStnV9lChoBkfAWgqMHbAUL2gHS/FoCEdAk9XBekYXPHV9lChoBkfAWly9K28Zk2gHTVwBaAhHQJPWeIxgy/N1fZQoaAZHwGDAinP3SKFoB01tAWgIR0CT2W84xUNsdX2UKGgGR8Bk8FTWGyooaAdNnwFoCEdAk9pH4j8k2XV9lChoBkfAZFuHv+fh/GgHTWkBaAhHQJPaQ2VE/jd1fZQoaAZHwFdl3JxNqQBoB008AWgIR0CT3RE0zj3mdX2UKGgGR8Bb+MfaHsTnaAdNjgFoCEdAk925VCHARHV9lChoBkfAWz+LYPGyX2gHTTQBaAhHQJPe1R3u/lB1fZQoaAZHwGi4XevZAY5oB01zAWgIR0CT4bVQhwERdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 14844, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "buffer_size": 1000000, "batch_size": 64, "learning_starts": 50000, "tau": 1.0, "gamma": 0.999, "gradient_steps": 1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==", "__module__": "stable_baselines3.common.buffers", "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ", "__init__": "<function ReplayBuffer.__init__ at 0x7ed0e49cecb0>", "add": "<function ReplayBuffer.add at 0x7ed0e49ced40>", "sample": "<function ReplayBuffer.sample at 0x7ed0e49cedd0>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7ed0e49cee60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ed0e49d3000>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.05, "exploration_fraction": 0.1, "target_update_interval": 62, "_n_calls": 62500, "max_grad_norm": 10, "exploration_rate": 0.05, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "exploration_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__module__": "stable_baselines3.dqn.policies", "__annotations__": "{'q_net': <class 'stable_baselines3.dqn.policies.QNetwork'>, 'q_net_target': <class 'stable_baselines3.dqn.policies.QNetwork'>}", "__doc__": "\n    Policy class with Q-Value Net and target net for DQN\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ", "__init__": "<function DQNPolicy.__init__ at 0x7e53234fa5f0>", "_build": "<function DQNPolicy._build at 0x7e53234fa680>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7e53234fa710>", "forward": "<function DQNPolicy.forward at 0x7e53234fa7a0>", "_predict": "<function DQNPolicy._predict at 0x7e53234fa830>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7e53234fa8c0>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7e53234fa950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e5323511640>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1691085597579096751, "learning_rate": 0.0001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAGAhFD6kr0y77z2dvA9kODojrqS84OIdOwAAgD8AAIA/wGE3vmGyIj/DAga+JSfxvdW0nLxVUk28AAAAAAAAAAC0Ixy/ELqUPoF6g713Fnq9pLn4Or5MKT0AAAAAAAAAAPP1rb4fTB0+9tMdvZwMGr3njhO8lSIxPQAAAAAAAAAAAzXovqACAT/QY129fHU8vWdK5byqAIE8AAAAAAAAAAAzwK6+cdjDPjYfVL3U+ji9W8UNvfY/9jsAAAAAAAAAAAXf0b6UfNI9bqcNvW61hr19W6W8puppPQAAAAAAAAAAGiIkvuBq9j7rCwi+NFSbvddnb70nDwk9AAAAAAAAAACaZ7u82ywjP7jvdL59slC+AKr8vBToM70AAAAAAAAAAABuwLxFq0s+FrxcvvlKqb1eXSi9xohCvQAAAAAAAAAAZq24voBcrD7Er7O7NFaKvUGceT3KQgQ9AAAAAAAAAADt12W+aXRlvLT+Hjw3Fws6UAbPPb0y47oAAIA/AACAP832xb3m1/w+axFVvv5SJr4pPI29MpQGvQAAAAAAAAAAs+WTPow6rT6Gp4a+UvUhvlZNZjwunh+9AAAAAAAAAABmocQ9yBHGPc755L3j+OK90b46vCEiBzwAAAAAAAAAAJpqm7xIz5C6boiBuM8udrPbyVI5cjCWNwAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 2984, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 14844, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "buffer_size": 1000000, "batch_size": 64, "learning_starts": 50000, "tau": 1.0, "gamma": 0.999, "gradient_steps": 1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==", "__module__": "stable_baselines3.common.buffers", "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ", "__init__": "<function ReplayBuffer.__init__ at 0x7e53234daa70>", "add": "<function ReplayBuffer.add at 0x7e53234dab00>", "sample": "<function ReplayBuffer.sample at 0x7e53234dab90>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7e53234dac20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e53234e32c0>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.05, "exploration_fraction": 0.5, "target_update_interval": 625, "_n_calls": 62500, "max_grad_norm": 10, "exploration_rate": 0.05, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "exploration_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -81.3038419, "std_reward": 90.74335505808797, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-08-03T17:35:36.023554"}
+{"mean_reward": 58.89065840000001, "std_reward": 158.77127406358528, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-08-03T18:21:04.369713"}