It seems that DQN performs the worst if trained for 1e6 timesteps. But it did train quicker, taking about 17 min, as opposed to 20-22.

DQN-1e6.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:773a97a02014766291687d02784337cab812a0d80c8597eea00692a4d7188a80
+size 110207

DQN-1e6/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.2

DQN-1e6/data

@@ -0,0 +1,117 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=",
+        "__module__": "stable_baselines3.dqn.policies",
+        "__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 0x7fcb08aa3790>",
+        "_build": "<function DQNPolicy._build at 0x7fcb08aa3820>",
+        "make_q_net": "<function DQNPolicy.make_q_net at 0x7fcb08aa38b0>",
+        "forward": "<function DQNPolicy.forward at 0x7fcb08aa3940>",
+        "_predict": "<function DQNPolicy._predict at 0x7fcb08aa39d0>",
+        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7fcb08aa3a60>",
+        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7fcb08aa3af0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7fcb08aab900>"
+    },
+    "verbose": true,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            8
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False]",
+        "bounded_above": "[False False False False False False False False]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "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",
+        "n": 4,
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": "RandomState(MT19937)"
+    },
+    "n_envs": 8,
+    "num_timesteps": 1000000,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1671128343611367066,
+    "learning_rate": 0.0001,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAEBAQEBAQEBlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="
+    },
+    "_last_original_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_episode_num": 2306,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": 0.0,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 29688,
+    "buffer_size": 1000000,
+    "batch_size": 32,
+    "learning_starts": 50000,
+    "tau": 1.0,
+    "gamma": 0.99,
+    "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 0x7fcb08a77b80>",
+        "add": "<function ReplayBuffer.add at 0x7fcb08a77c10>",
+        "sample": "<function ReplayBuffer.sample at 0x7fcb08a77ca0>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fcb08a77d30>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7fcb08a7ef40>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
+    },
+    "actor": null,
+    "use_sde_at_warmup": false,
+    "exploration_initial_eps": 1.0,
+    "exploration_final_eps": 0.05,
+    "exploration_fraction": 0.1,
+    "target_update_interval": 156,
+    "_n_calls": 125000,
+    "max_grad_norm": 10,
+    "exploration_rate": 0.05,
+    "exploration_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "batch_norm_stats": [],
+    "batch_norm_stats_target": []
+}

DQN-1e6/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3389b586a35b1064133d2658ec0604364444a55fbc129239a24524c29e3355a8
+size 44975

DQN-1e6/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ac8d5f020131e906a9b809bbb9f3cfa00be73acbeb313a2a43759e58927ffad1
+size 44033

DQN-1e6/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

DQN-1e6/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.4.0-135-generic-x86_64-with-glibc2.31 #152-Ubuntu SMP Wed Nov 23 20:19:22 UTC 2022
+Python: 3.9.16
+Stable-Baselines3: 1.6.2
+PyTorch: 1.13.0+cu117
+GPU Enabled: True
+Numpy: 1.23.5
+Gym: 0.21.0

README.md

@@ -6,7 +6,7 @@ tags:
 - reinforcement-learning
 - stable-baselines3
 model-index:
-- name: A2C
+- name: DQN
   results:
   - task:
       type: reinforcement-learning
@@ -16,13 +16,13 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -14.54 +/- 125.39
+      value: -29.89 +/- 28.12
       name: mean_reward
       verified: false
 ---
 
-# **A2C** Agent playing **LunarLander-v2**
-This is a trained model of a **A2C** agent playing **LunarLander-v2**
+# **DQN** Agent playing **LunarLander-v2**
+This is a trained model of a **DQN** agent playing **LunarLander-v2**
 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
 
 ## Usage (with Stable-baselines3)

config.json

@@ -1 +1 @@
-{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\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 ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\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 ActorCriticPolicy.__init__ at 0x7f61c5abb1f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f61c5abb280>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f61c5abb310>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f61c5abb3a0>", "_build": "<function ActorCriticPolicy._build at 0x7f61c5abb430>", "forward": "<function ActorCriticPolicy.forward at 0x7f61c5abb4c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f61c5abb550>", "_predict": "<function ActorCriticPolicy._predict at 0x7f61c5abb5e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f61c5abb670>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f61c5abb700>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f61c5abb790>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f61c5abc500>"}, "verbose": true, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 8, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671126853057320473, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 25000, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": false, "target_kl": null, "system_info": {"OS": "Linux-5.4.0-135-generic-x86_64-with-glibc2.31 #152-Ubuntu SMP Wed Nov 23 20:19:22 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu117", "GPU Enabled": "True", "Numpy": "1.23.5", "Gym": "0.21.0"}}
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__module__": "stable_baselines3.dqn.policies", "__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 0x7fcb08aa3790>", "_build": "<function DQNPolicy._build at 0x7fcb08aa3820>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7fcb08aa38b0>", "forward": "<function DQNPolicy.forward at 0x7fcb08aa3940>", "_predict": "<function DQNPolicy._predict at 0x7fcb08aa39d0>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7fcb08aa3a60>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7fcb08aa3af0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fcb08aab900>"}, "verbose": true, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "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", "n": 4, "_shape": [], "dtype": "int64", "_np_random": "RandomState(MT19937)"}, "n_envs": 8, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671128343611367066, "learning_rate": 0.0001, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAEBAQEBAQEBlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQEAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAQAAAAAAADPg4Lxooy4/HoCJPdatOL74mm493n/juwAAAAAAAAAAfcf7vklBQj8yayY+IXxVvgiEA75ipYw8AAAAAAAAAABNqZ69tbaaPyKom7zmE0K6TH3kvO40QLsAAAAAAAAAAB6M377o/PQ+zirxPiqinb7/8OE8mpyTPQAAAAAAAAAAqPS1viPxHD9NUNU+ZSuxvpnGyL1p8zY9AAAAAAAAAADNZDk95zdRP0JwLb63Nx6+WSf6vDKpPTsAAAAAAAAAAKY8s77Hybw+xubdPn0Srb6aAaW7oNZPPQAAAAAAAAAAmnHYPKPmcT8bQ00+0W4GvpYzMbwmH049AAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwhLCIaUjAFDlHSUUpQu"}, "_episode_num": 2306, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 29688, "buffer_size": 1000000, "batch_size": 32, "learning_starts": 50000, "tau": 1.0, "gamma": 0.99, "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 0x7fcb08a77b80>", "add": "<function ReplayBuffer.add at 0x7fcb08a77c10>", "sample": "<function ReplayBuffer.sample at 0x7fcb08a77ca0>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7fcb08a77d30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fcb08a7ef40>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "actor": null, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.05, "exploration_fraction": 0.1, "target_update_interval": 156, "_n_calls": 125000, "max_grad_norm": 10, "exploration_rate": 0.05, "exploration_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "system_info": {"OS": "Linux-5.4.0-135-generic-x86_64-with-glibc2.31 #152-Ubuntu SMP Wed Nov 23 20:19:22 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu117", "GPU Enabled": "True", "Numpy": "1.23.5", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -14.537485542119938, "std_reward": 125.38919961065463, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-15T20:16:04.295812"}
+{"mean_reward": -29.892793940205593, "std_reward": 28.12063664298142, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-15T20:38:34.501158"}