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HumanoidTTT

Reinforcement Learning
PyTorch
robotics
humanoid
double-dqn
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HumanoidTTT
File size: 2,330 Bytes
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{
  "format_version": 1,
  "algorithm": "Double-DQN",
  "checkpoint": "consolidation_policy.pt",
  "checkpoint_sha256": "cdb1b5f4f9c671da5c6c26f9d9cc752aee3c81fc87b40dad67d0efa02f0e60b5",
  "checkpoint_stage": "before_online_adaptation",
  "initialization_seed": 83001,
  "architecture": [
    71,
    128,
    64,
    1
  ],
  "hidden_activation": "ReLU",
  "parameter_count": 17537,
  "dtype": "float32",
  "state_dict_format": "raw_pytorch_state_dict",
  "capacity": 10,
  "recent_request_window": 16,
  "action_count_when_full": 11,
  "actions": {
    "0": "SKIP",
    "1..10": "REPLACE(entries[action_index - 1])"
  },
  "api_action_labels": {
    "SKIP": "DROP",
    "REPLACE": "REPLACE",
    "free_slot": "INSERT"
  },
  "feature_layout": [
    {
      "slice": [
        0,
        16
      ],
      "name": "candidate_motion_descriptor"
    },
    {
      "slice": [
        16,
        32
      ],
      "name": "store_descriptor_mean"
    },
    {
      "slice": [
        32,
        48
      ],
      "name": "store_descriptor_max"
    },
    {
      "slice": [
        48,
        64
      ],
      "name": "replacement_target_descriptor_or_zeros_for_skip"
    },
    {
      "slice": [
        64,
        69
      ],
      "name": "global_features",
      "fields": [
        "store_size_div_20",
        "recent_unique_count_div_16",
        "candidate_recent_frequency",
        "mean_candidate_store_distance_div_20",
        "min_full_store_decisions_20_div_20"
      ]
    },
    {
      "slice": [
        69,
        71
      ],
      "name": "action_features",
      "fields": [
        "is_skip",
        "target_recent_frequency"
      ]
    }
  ],
  "online_learning_rate": 3e-05,
  "gamma": 0.95,
  "optimizer": "Adam",
  "loss": "smooth_l1",
  "gradient_norm_clip": 5.0,
  "target_sync_optimizer_steps": 50,
  "replay_min_transitions": 8,
  "replay_draws_per_update_call": 8,
  "reward": "successful reuse count / request count between consecutive full-store qualified-miss decisions",
  "reward_input": "observe_request(capability_id, reused=successful_reuse)",
  "code_repository": "https://github.com/AIGeeksGroup/HumaniodTTT",
  "verified_source_commit": "39f33575fff8378c0cabf4571b595646d833667c"
}