\n1. \uc11c\ub860<\/h2>\n \uac15\ud654\ud559\uc2b5(Deep Reinforcement Learning, DRL)\uc740 \ubcf5\uc7a1\ud55c \ud658\uacbd\uc5d0\uc11c \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \ud559\uc2b5\ud558\uae30 \uc704\ud55c \uac15\ub825\ud55c \ub3c4\uad6c\uc785\ub2c8\ub2e4. \uadf8\ub7ec\ub098 \uc774\ub7ec\ud55c \ud559\uc2b5 \uacfc\uc815\uc740 \ub9e4\uc6b0 \ube44\ud6a8\uc728\uc801\uc77c \uc218 \uc788\uc73c\uba70, \ud2b9\ud788 \ud559\uc2b5\ud558\ub294 \uc5d0\uc774\uc804\ud2b8\uac00 \ucc98\uc74c\ubd80\ud130 \ubcf5\uc7a1\ud55c \uc791\uc5c5\uc744 \ucc98\ub9ac\ud574\uc57c \ud560 \uacbd\uc6b0 \ub354\uc6b1 \uadf8\ub7ec\ud569\ub2c8\ub2e4. \uc774\ub97c \ud574\uacb0\ud558\uae30 \uc704\ud55c \uc811\uadfc \ubc29\ubc95 \uc911 \ud558\ub098\uac00 \ubc14\ub85c \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5(Curriculum Learning)\uc785\ub2c8\ub2e4. \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc740 \uac04\ub2e8\ud55c \uc791\uc5c5\ubd80\ud130 \uc2dc\uc791\ud558\uc5ec \uc810\uc9c4\uc801\uc73c\ub85c \uc5b4\ub824\uc6b4 \uc791\uc5c5\uc73c\ub85c \ub098\uc544\uac00\ub294 \ubc29\ubc95\ub860\uc73c\ub85c, \uc5d0\uc774\uc804\ud2b8\uac00 \ub354 \ube60\ub974\uace0 \uc548\uc815\uc801\uc73c\ub85c \ud559\uc2b5\ud560 \uc218 \uc788\ub3c4\ub85d \ub3c4\uc640\uc90d\ub2c8\ub2e4.<\/p>\n<\/section>\n\n2. \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc758 \uc6d0\ub9ac<\/h2>\n \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc740 \uad50\uc721\uc758 \uc6d0\ub9ac\uc5d0\uc11c \uc601\uac10\uc744 \ubc1b\uc544 \ub9cc\ub4e4\uc5b4\uc84c\uc2b5\ub2c8\ub2e4. \uc778\uac04\uc774 \ud559\uc2b5\ud560 \ub54c, \ud1b5\uc0c1\uc801\uc73c\ub85c \uac04\ub2e8\ud55c \uac1c\ub150\ubd80\ud130 \ubc30\uc6b0\uace0, \uc774\ud6c4 \uc810\ucc28 \ubcf5\uc7a1\ud55c \uac1c\ub150\uc73c\ub85c \ub098\uc544\uac00\ub294 \uacfc\uc815\uc744 \ub530\ub985\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc6d0\ub9ac\ub294 \uae30\uacc4 \ud559\uc2b5\uc5d0\ub3c4 \uc720\uc0ac\ud558\uac8c \uc801\uc6a9\ub420 \uc218 \uc788\uc73c\uba70, \uc5d0\uc774\uc804\ud2b8\uac00 \uae34 \uc218\uba85 \ub3d9\uc548 \ub2e4\uc591\ud55c \uacbd\ud5d8\uc744 \ucd95\uc801\ud558\uac8c \ud568\uc73c\ub85c\uc368 \ud559\uc2b5 \ud6a8\uc728\uc744 \ub192\uc774\ub294 \ub370 \uae30\uc5ec\ud569\ub2c8\ub2e4.<\/p>\n
\ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc758 \uae30\ubcf8 \uc6d0\ub9ac\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n
\n\uc810\uc9c4\uc801\uc778 \ud559\uc2b5:<\/strong> \ucc98\uc74c\uc5d0\ub294 \uc27d\uace0 \uac04\ub2e8\ud55c \uc791\uc5c5\uc73c\ub85c \uc2dc\uc791\ud558\uc5ec, \uc810\ucc28 \ub09c\uc774\ub3c4\uac00 \uc99d\uac00\ud558\ub294 \uc791\uc5c5\uc73c\ub85c \ub118\uc5b4\uac11\ub2c8\ub2e4. \uc774\ub7f0 \uc810\uc9c4\uc801\uc778 \uc811\uadfc\uc740 \uc5d0\uc774\uc804\ud2b8\uc758 \uc548\uc815\uc131\uc744 \ub192\uc774\uba70, \uadf9\ub2e8\uc801\uc778 \uc0c1\ud669\uc5d0 \ub300\ud55c \ucc98\ub9ac\ub97c \ub354 \uc798 \ud560 \uc218 \uc788\uac8c \ub9cc\ub4ed\ub2c8\ub2e4.<\/li>\n\uc791\uc5c5\uc758 \ub2e4\uc591\uc131:<\/strong> \ub2e4\uc591\ud55c \ub09c\uc774\ub3c4\uc758 \uc791\uc5c5\uc744 \ud1b5\ud574 \uc5d0\uc774\uc804\ud2b8\ub294 \ub2e4\uc591\ud55c \uacbd\ud5d8\uc744 \ud560 \uc218 \uc788\uc73c\uba70, \uc774\ub294 \uc77c\ubc18\ud654 \ub2a5\ub825\uc744 \ud5a5\uc0c1\uc2dc\ud0b5\ub2c8\ub2e4.<\/li>\n\uac00\uc911\uce58 \ucd08\uae30\ud654 \ubc0f \ud559\uc2b5 \uc18d\ub3c4 \ud5a5\uc0c1:<\/strong> \ucd08\uae30\uc5d0\ub294 \ub2e8\uc21c\ud55c \ubb38\uc81c\ub97c \ud574\uacb0\ud558\uace0, \uc774\ub97c \ud1b5\ud574 \ubaa8\ub378\uc758 \uac00\uc911\uce58\ub97c \ud6e8\uc52c \uc27d\uac8c \ucd08\uae30\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ud6c4 \ubcf4\ub2e4 \ubcf5\uc7a1\ud55c \ubb38\uc81c\ub97c \ud574\uacb0\ud560 \ub54c \uc774\ub7ec\ud55c \ucd08\uae30\ud654\ub41c \uac00\uc911\uce58\uac00 \ub3c4\uc6c0\uc744 \uc904 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/section>\n\n3. \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc758 \uc7a5\uc810<\/h2>\n \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc5d0\ub294 \uc5ec\ub7ec \uac00\uc9c0 \uc7a5\uc810\uc774 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n
\n\ud559\uc2b5 \uc18d\ub3c4 \ud5a5\uc0c1:<\/strong> \uc27d\uac8c \ud574\uacb0\ud560 \uc218 \uc788\ub294 \ubb38\uc81c\ubd80\ud130 \uac1c\ubc1c\ud558\uba74, \uc5d0\uc774\uc804\ud2b8\uac00 \ud559\uc2b5\ud558\ub294 \uc18d\ub3c4\uac00 \ube68\ub77c\uc9d1\ub2c8\ub2e4. \uac04\ub2e8\ud55c \uc791\uc5c5\uc5d0\uc11c \uc5bb\uc740 \uc9c0\uc2dd\uc774 \ub354 \ubcf5\uc7a1\ud55c \uc791\uc5c5 \uad6c\uc131 \uc2dc\uc5d0\ub3c4 \uc0ac\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n\uc131\ub2a5 \ud5a5\uc0c1:<\/strong> \uc5ec\ub7ec \ub2e8\uacc4\ub85c \ub098\ub204\uc5b4 \ud559\uc2b5\ud558\ub2e4 \ubcf4\uba74 \uc5d0\uc774\uc804\ud2b8\ub294 \uac01 \ub2e8\uacc4\uc5d0\uc11c\uc758 \uc9c0\uc2dd\uc744 \ubc14\ud0d5\uc73c\ub85c \ub354 \ub192\uc740 \uc131\ub2a5\uc744 \ubc1c\ud718\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub294 \ud2b9\ud788 \ubcf5\uc7a1\ud55c \ud658\uacbd\uc5d0\uc11c \uc774\uc810\uc744 \uac00\uc838\uc635\ub2c8\ub2e4.<\/li>\n\uc548\uc815\uc131 \ubc0f \uc77c\ubc18\ud654:<\/strong> \ub2e4\uc591\ud55c \ub09c\uc774\ub3c4\uc758 \uc791\uc5c5\uc744 \ud1b5\ud574 \uc5d0\uc774\uc804\ud2b8\uac00 \ub354 \ub9ce\uc740 \uacbd\ud5d8\uc744 \uc313\uac8c \ub418\uba70, \uc774\ub97c \ud1b5\ud574 \ub2e4\uc591\ud55c \uc0c1\ud669\uc5d0 \ub300\ud574 \uc77c\ubc18\ud654\ud560 \uc218 \uc788\uac8c \ub429\ub2c8\ub2e4.<\/li>\n\uc790\uc6d0 \ud6a8\uc728\uc131:<\/strong> \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc744 \ud1b5\ud574 \uc5d0\uc774\uc804\ud2b8\ub294 \ud544\uc694\ud55c \uc790\uc6d0\uc744 \ud6a8\uc728\uc801\uc73c\ub85c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubb34\uc791\uc815 \uc5b4\ub824\uc6b4 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub824\ub294 \uac83\ubcf4\ub2e4, \ucc28\uadfc\ucc28\uadfc \uacf5\ubd80\ud558\ub294 \uac83\uc774 \uc790\uc6d0 \ubc0f \uc2dc\uac04 \uce21\uba74\uc5d0\uc11c \ud6a8\uc728\uc801\uc785\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/section>\n\n4. \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5 \uad6c\ud604 \uc608\uc81c<\/h2>\n \uc774\uc81c \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc744 \uc2e4\uc81c Python \ucf54\ub4dc\ub85c \uad6c\ud604\ud558\ub294 \ubc29\ubc95\uc744 \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\ub294 OpenAI\uc758 Gym \ud658\uacbd\uc744 \ud65c\uc6a9\ud558\uc5ec \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc744 \uad6c\ud604\ud558\ub294 \uae30\ubcf8\uc801\uc778 \ud2c0\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/p>\n
4.1. \ud658\uacbd \uc900\ube44<\/h3>\n \uba3c\uc800 \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud558\uace0 \ud544\uc694\ud55c \ud658\uacbd\uc744 \uc124\uc815\ud569\ub2c8\ub2e4. Gym\uacfc RLlib\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \uc791\uc5c5\uc744 \uad6c\uc131\ud569\ub2c8\ub2e4.<\/p>\n
!pip install gym\n!pip install ray[rllib]<\/code><\/pre>\n4.2. \uac04\ub2e8\ud55c \ud658\uacbd \uc124\uc815<\/h3>\n \uc5ec\uae30\uc11c\ub294 CartPole \ubb38\uc81c\ub97c \uc608\ub85c \ub4e4\uaca0\uc2b5\ub2c8\ub2e4. CartPole\uc740 \uc5d0\uc774\uc804\ud2b8\uac00 \ub9c9\ub300\ub97c \uc138\uc6b4 \ucc44\ub85c \uce74\ud2b8\ub97c \uc81c\uc5b4\ud558\ub294 \ubb38\uc81c\uc785\ub2c8\ub2e4. \ucd08\uae30 \uac04\ub2e8\ud55c \ubc84\uc804\uc744 \uc124\uc815\ud569\ub2c8\ub2e4.<\/p>\n
import gym\n\ndef create_env(env_name):\n return gym.make(env_name)\n\nenv = create_env('CartPole-v1')<\/code><\/pre>\n4.3. \ucee4\ub9ac\ud058\ub7fc \uc815\uc758\ud558\uae30<\/h3>\n \uc5ec\uae30\uc5d0\uc11c \uc6b0\ub9ac\ub294 \ucee4\ub9ac\ud058\ub7fc\uc744 \ub9cc\ub4e4\uc5b4 \uc5d0\uc774\uc804\ud2b8\uac00 \ud559\uc2b5\ud560 \ub2e8\uacc4\uc801\uc778 \uc791\uc5c5\uc744 \uc815\uc758\ud569\ub2c8\ub2e4.<\/p>\n
def curriculum():\n return [\n {'name': 'easy', 'max_steps': 50}, # \uc26c\uc6b4 \ub2e8\uacc4\n {'name': 'medium', 'max_steps': 100}, # \uc911\uac04 \ub2e8\uacc4\n {'name': 'hard', 'max_steps': 200}, # \uc5b4\ub824\uc6b4 \ub2e8\uacc4\n ]\n\ncurriculum_stages = curriculum()<\/code><\/pre>\n4.4. \uc5d0\uc774\uc804\ud2b8 \ud559\uc2b5 \ub8e8\ud504<\/h3>\n \uac01 \ucee4\ub9ac\ud058\ub7fc \ub2e8\uacc4\ub97c \ud1b5\ud574 \uc5d0\uc774\uc804\ud2b8\ub97c \ud559\uc2b5\ud558\ub294 \uba54\uc778 \ub8e8\ud504\ub97c \ub9cc\ub4ed\ub2c8\ub2e4.<\/p>\n
import numpy as np\n\ndef train_agent(env, curriculum_stages):\n for stage in curriculum_stages:\n print(f\"Training on stage: {stage['name']}\")\n for episode in range(100): # \uac01 \ub2e8\uacc4\uc5d0\uc11c 100\ubc88\uc758 \uc5d0\ud53c\uc18c\ub4dc \ud559\uc2b5\n state = env.reset()\n done = False\n steps = 0\n while not done and steps < stage['max_steps']:\n action = env.action_space.sample() # \ub79c\ub364 \ud589\ub3d9 \uc120\ud0dd\n next_state, reward, done, info = env.step(action)\n state = next_state\n steps += 1\n\ntrain_agent(env, curriculum_stages)<\/code><\/pre>\n4.5. \ud559\uc2b5 \uacb0\uacfc \ud3c9\uac00<\/h3>\n \ud559\uc2b5\uc774 \ub05d\ub09c \ud6c4, \uc131\ub2a5\uc744 \ud3c9\uac00\ud558\uc5ec \ucee4\ub9ac\ud058\ub7fc\uc758 \ud6a8\uacfc\ub97c \ud655\uc778\ud569\ub2c8\ub2e4. \ud3c9\uac00\ub97c \uc704\ud574 \ud559\uc2b5\ub41c \uc5d0\uc774\uc804\ud2b8\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubb38\uc81c\ub97c \ud574\uacb0\ud569\ub2c8\ub2e4.<\/p>\n
def evaluate_agent(env, trained_agent):\n state = env.reset()\n done = False\n total_rewards = 0\n while not done:\n action = trained_agent.act(state) # \ud559\uc2b5\ub41c \uc815\ucc45\uc5d0 \ub530\ub77c \ud589\ub3d9\n state, reward, done, _ = env.step(action)\n total_rewards += reward\n return total_rewards\n\n# \uc774\ub97c \ud1b5\ud574 \uc5d0\uc774\uc804\ud2b8 \ud3c9\uac00\nscore = evaluate_agent(env, trained_agent)\nprint(f\"Trained agent score: {score}\")<\/code><\/pre>\n<\/section>\n\n5. \uacb0\ub860<\/h2>\n \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc740 \uac15\ud654\ud559\uc2b5\uc5d0\uc11c \ub9e4\uc6b0 \uc911\uc694\ud55c \uc811\uadfc\ubc95\uc73c\ub85c, \uc5d0\uc774\uc804\ud2b8\uac00 \ud6a8\uc728\uc801\uc73c\ub85c \ud559\uc2b5\ud558\uace0 \uc131\ub2a5\uc744 \ud5a5\uc0c1\uc2dc\ud0ac \uc218 \uc788\uac8c \ud569\ub2c8\ub2e4. \uac04\ub2e8\ud55c \uc791\uc5c5\uc5d0\uc11c \uc2dc\uc791\ud558\uc5ec \uc810\ucc28 \ub09c\uc774\ub3c4\ub97c \ub192\uc774\ub294 \uac83\uc740 \uc790\uc5f0\uc2a4\ub7ec\uc6b4 \ud559\uc2b5 \uacfc\uc815\uc774\uba70, \uc774\ub294 \uc5d0\uc774\uc804\ud2b8\uc758 \uc77c\ubc18\ud654 \ub2a5\ub825\uc744 \uac15\ud654\ud558\ub294 \ub370 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4. \uc774 \uac15\uc88c\uc5d0\uc11c \uc18c\uac1c\ud55c \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc758 \uc6d0\ub9ac\uc640 \uc7a5\uc810\uc744 \uc774\ud574\ud558\uace0, Python \ucf54\ub4dc\ub97c \ud1b5\ud574 \uad6c\ud604\ud574\ubcf4\uba74\uc11c \uc2e4\uc9c8\uc801\uc778 \uacbd\ud5d8\uc744 \uc313\uae38 \ubc14\ub78d\ub2c8\ub2e4. \uc55e\uc73c\ub85c\ub3c4 \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc744 \ud1b5\ud574 \ub354 \ub098\uc740 \uac15\ud654\ud559\uc2b5 \ubaa8\ub378\ub4e4\uc744 \uac1c\ubc1c\ud560 \uc218 \uc788\uae30\ub97c \uae30\ub300\ud569\ub2c8\ub2e4.<\/p>\n<\/section>\n\n\uac10\uc0ac\ud569\ub2c8\ub2e4!<\/p>\n<\/footer>\n<\/article>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
\uc791\uc131\uc790: \uc870\uad11\ud615 \ub0a0\uc9dc: 2024\ub144 11\uc6d4 26\uc77c 1. \uc11c\ub860 \uac15\ud654\ud559\uc2b5(Deep Reinforcement Learning, DRL)\uc740 \ubcf5\uc7a1\ud55c \ud658\uacbd\uc5d0\uc11c \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \ud559\uc2b5\ud558\uae30 \uc704\ud55c \uac15\ub825\ud55c \ub3c4\uad6c\uc785\ub2c8\ub2e4. \uadf8\ub7ec\ub098 \uc774\ub7ec\ud55c \ud559\uc2b5 \uacfc\uc815\uc740 \ub9e4\uc6b0 \ube44\ud6a8\uc728\uc801\uc77c \uc218 \uc788\uc73c\uba70, \ud2b9\ud788 \ud559\uc2b5\ud558\ub294 \uc5d0\uc774\uc804\ud2b8\uac00 \ucc98\uc74c\ubd80\ud130 \ubcf5\uc7a1\ud55c \uc791\uc5c5\uc744 \ucc98\ub9ac\ud574\uc57c \ud560 \uacbd\uc6b0 \ub354\uc6b1 \uadf8\ub7ec\ud569\ub2c8\ub2e4. \uc774\ub97c \ud574\uacb0\ud558\uae30 \uc704\ud55c \uc811\uadfc \ubc29\ubc95 \uc911 \ud558\ub098\uac00 \ubc14\ub85c \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5(Curriculum Learning)\uc785\ub2c8\ub2e4. \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc740 \uac04\ub2e8\ud55c \uc791\uc5c5\ubd80\ud130 \uc2dc\uc791\ud558\uc5ec … \ub354 \ubcf4\uae30 “33. \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5(Curriculum Learning)\uc73c\ub85c \ub2e8\uacc4\uc801 \ud559\uc2b5 \uad6c\ud604\ud558\uae30, \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc758 \uc6d0\ub9ac\uc640 \uc7a5\uc810”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[213],"tags":[],"class_list":["post-40484","post","type-post","status-publish","format-standard","hentry","category-213"],"yoast_head":"\n33. \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5(Curriculum Learning)\uc73c\ub85c \ub2e8\uacc4\uc801 \ud559\uc2b5 \uad6c\ud604\ud558\uae30, \ucee4\ub9ac\ud058\ub7fc \ud559\uc2b5\uc758 \uc6d0\ub9ac\uc640 \uc7a5\uc810 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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\uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc740 \ub9ce\uc740 \ud22c\uc790\uc790\uc640 \ud000\ud2b8\ub4e4\uc774 \uc801\uc6a9\ud558\uace0 \uc788\uc73c\uba70, \uadf8 \uac00\ub2a5\uc131\uc740 \ubb34\uad81\ubb34\uc9c4\ud569\ub2c8\ub2e4. \ubcf8 \uae00\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uae30\ucd08\ubd80\ud130 \uace0\uae09 \uc8fc\uc81c\uc778 \ud45c\ubcf8 \uc678 \uc218\uc775\ub960 \ubd84\uc11d(Out-of-Sample Return Analysis)\uae4c\uc9c0\ub97c \uc2ec\ub3c4 \uae4a\uac8c \ub2e4\ub8e8\uc5b4 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. 1. \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\u2026","rel":"","context":""\ub525\ub7ec\ub2dd \uba38\uc2e0\ub7ec\ub2dd \uc790\ub3d9 \ud2b8\ub808\uc774\ub529"\uc5d0\uc11c","block_context":{"text":"\ub525\ub7ec\ub2dd \uba38\uc2e0\ub7ec\ub2dd \uc790\ub3d9 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