\ud63c\ud569(Mixed):<\/strong> \uc77c\ubd80 \uc5d0\uc774\uc804\ud2b8\ub294 \ud611\ub825\ud558\uace0 \uc77c\ubd80\ub294 \uacbd\uc7c1\ud558\ub294 \ubc29\uc2dd\uc73c\ub85c \uad6c\uc131\ub429\ub2c8\ub2e4.<\/li>\n<\/ul>\n2. \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc758 \uc774\ub860\uc801 \ubc30\uacbd<\/h2>\n
\n \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc5d0\uc11c\ub294 \uc5ec\ub7ec \uc5d0\uc774\uc804\ud2b8\uac00 \ud658\uacbd\uacfc \uc0c1\ud638\uc791\uc6a9\ud558\ub294 \uacfc\uc815\uc5d0\uc11c \ubc1c\uc0dd\ud558\ub294 \ubb38\uc81c\ub4e4\uc774 \uc874\uc7ac\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ubb38\uc81c\ub4e4\uc740 \uc77c\ubc18\uc801\uc73c\ub85c \ub2e8\uc77c \uc5d0\uc774\uc804\ud2b8 \ud658\uacbd\uc5d0\uc11c \uac04\ub2e8\ud558\uac8c \ud574\uacb0\ub418\uc9c0\ub9cc, \ub2e4\uc218\uc758 \uc5d0\uc774\uc804\ud2b8\uac00 \uc874\uc7ac\ud558\uba74 \uc0c1\ud669\uc774 \ubcf5\uc7a1\ud574\uc9d1\ub2c8\ub2e4.\n<\/p>\n
2.1 \uc0c1\ud0dc-\ud589\ub3d9 \uac00\uce58 \ud568\uc218 (Q-\ud568\uc218)<\/h3>\n
\n \uac01 \uc5d0\uc774\uc804\ud2b8\ub294 Q-\ud568\uc218\ub97c \ud1b5\ud574 \uc0c1\ud0dc\uc640 \ud589\ub3d9\uc758 \uac00\uce58\ub97c \ud3c9\uac00\ud569\ub2c8\ub2e4. Q-\ud568\uc218\ub294 \ub2e4\uc74c\uacfc \uac19\uc774 \uc815\uc758\ub429\ub2c8\ub2e4:\n<\/p>\n
Qi<\/sub>(s, a) = E[R(t) | s(t)=s, a(t)=a]<\/p>\n\uc5ec\uae30\uc11c, Qi<\/sub>(s, a)\ub294 \uc5d0\uc774\uc804\ud2b8 i\uac00 \uc0c1\ud0dc s\uc5d0\uc11c \ud589\ub3d9 a\ub97c \uc120\ud0dd\ud588\uc744 \ub54c \uc608\uc0c1\ub418\ub294 \ubcf4\uc0c1\uc785\ub2c8\ub2e4.<\/p>\n2.2 \uc815\ucc45 \ucd5c\uc801\ud654<\/h3>\n
\n \uc5d0\uc774\uc804\ud2b8\ub294 \uc790\uc2e0\uc758 \uc815\ucc45\uc744 \ud1b5\ud574 \ud658\uacbd\uc5d0 \ub300\ud55c \ud589\ub3d9\uc744 \uc120\ud0dd\ud569\ub2c8\ub2e4. \uc815\ucc45 \ucd5c\uc801\ud654\ub294 \ubcf4\uc0c1\uc744 \uadf9\ub300\ud654\ud558\uae30 \uc704\ud55c \uc911\uc694\ud55c \uacfc\uc815\uc774\uba70, \ub2e4\uc74c\uacfc \uac19\uc740 \ubc29\ubc95\uc73c\ub85c \uc774\ub8e8\uc5b4\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4:\n<\/p>\n
\n- \uadf8\ub77c\ub514\uc5b8\ud2b8 \uae30\ubc18 \ubc29\ubc95:<\/strong> \uc815\ucc45\uc758 \ud30c\ub77c\ubbf8\ud130\ub97c \uc5c5\ub370\uc774\ud2b8\ud558\uae30 \uc704\ud574 \uadf8\ub798\ub514\uc5b8\ud2b8 \uc815\ubcf4\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/li>\n
- \uac12 \uae30\ubc18 \ubc29\ubc95:<\/strong> \uc5d0\uc774\uc804\ud2b8\ub294 \uc790\uc2e0\uc758 Q-\ud568\uc218\ub97c \uc5c5\ub370\uc774\ud2b8\ud558\uace0, \uc774\ub97c \ud1b5\ud574 \ucd5c\uc801\uc758 \uc815\ucc45\uc744 \uad6c\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n
3. \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5 \uc54c\uace0\ub9ac\uc998<\/h2>\n
\n \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc744 \uc704\ud55c \uc5ec\ub7ec \uc54c\uace0\ub9ac\uc998\ub4e4\uc774 \uac1c\ubc1c\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc11c\ub294 \uc77c\ubd80 \ub300\ud45c\uc801\uc778 \uc54c\uace0\ub9ac\uc998\ub4e4\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4.\n<\/p>\n
3.1 \ub3c5\ub9bd\uc801 Q-\ud559\uc2b5 (Independent Q-Learning)<\/h3>\n
\n \ub3c5\ub9bd\uc801 Q-\ud559\uc2b5\uc740 \uac01 \uc5d0\uc774\uc804\ud2b8\uac00 \uc790\uc2e0\uc758 Q-\ud568\uc218\ub97c \ub3c5\ub9bd\uc801\uc73c\ub85c \uc5c5\ub370\uc774\ud2b8\ud558\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4. \uc774 \ubc29\uc2dd\uc740 \ub2e8\uc21c\ud558\uc9c0\ub9cc, \ub2e4\ub978 \uc5d0\uc774\uc804\ud2b8\uc758 \uc601\ud5a5\uc744 \ubb34\uc2dc\ud558\uac8c \ub418\uc5b4 \uc218\ub834 \uc18d\ub3c4\uac00 \ub290\ub824\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n<\/p>\n
3.2 \uacf5\ub3d9 Q-\ud559\uc2b5 (Cooperative Q-Learning)<\/h3>\n
\n \uacf5\ub3d9 Q-\ud559\uc2b5\uc5d0\uc11c\ub294 \uc5d0\uc774\uc804\ud2b8\ub4e4\uc774 \uacf5\uc720\ub41c Q-\ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uba70, \uac01 \uc5d0\uc774\uc804\ud2b8\ub294 \ub2e4\ub978 \uc5d0\uc774\uc804\ud2b8\uc758 \ud589\ub3d9\uc744 \uace0\ub824\ud558\uc5ec \uc790\uc2e0\uc758 Q-\ud568\uc218\ub97c \uc5c5\ub370\uc774\ud2b8\ud569\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \ud611\ub825\ud559\uc2b5\uc774 \uac00\ub2a5\ud574\uc9d1\ub2c8\ub2e4.\n<\/p>\n
3.3 \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \ub525 \uac15\ud654\ud559\uc2b5 (Multi-Agent Deep RL)<\/h3>\n
\n \ucd5c\uadfc\uc5d0\ub294 \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5 \uae30\ubc95\ub4e4\uc774 \ub9ce\uc774 \uc5f0\uad6c\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. DDPG(Deep Deterministic Policy Gradient), MADDPG(Multi-Agent Deep Deterministic Policy Gradient)\uc640 \uac19\uc740 \uc54c\uace0\ub9ac\uc998\uc774 \uc774\uc5d0 \ud574\ub2f9\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc54c\uace0\ub9ac\uc998\uc740 \uc0c1\ud0dc \uacf5\uac04\uc774 \ud06c\uac8c \ud655\uc7a5\ub420 \ub54c \ud6a8\uacfc\uc801\uc785\ub2c8\ub2e4.\n<\/p>\n
4. \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc758 \uc2e4\uc81c \uc801\uc6a9 \uc0ac\ub840<\/h2>\n
\n \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc740 \uc5ec\ub7ec \ubd84\uc57c\uc5d0\uc11c \uc2e4\uc81c\ub85c \uc801\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc11c\ub294 \uba87 \uac00\uc9c0 \ub300\ud45c\uc801\uc778 \uc0ac\ub840\ub97c \uc18c\uac1c\ud558\uaca0\uc2b5\ub2c8\ub2e4.\n<\/p>\n
4.1 \uc790\uc728\uc8fc\ud589\ucc28<\/h3>\n
\n \uc790\uc728\uc8fc\ud589\ucc28\uc758 \uacbd\uc6b0, \uc5ec\ub7ec \ub300\uc758 \ucc28\ub7c9\uc774 \ub3d9\uc2dc\uc5d0 \ub3c4\ub85c\ub97c \uc8fc\ud589\ud569\ub2c8\ub2e4. \uc774\ub54c \uac01\uac01\uc758 \ucc28\ub7c9\uc740 \ub2e4\ub978 \ucc28\ub7c9\uacfc\uc758 \uc0c1\ud638\uc791\uc6a9\uc744 \uace0\ub824\ud558\uc5ec \uc8fc\ud589 \uacbd\ub85c\ub97c \uacb0\uc815\ud574\uc57c \ud569\ub2c8\ub2e4. \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc744 \ud1b5\ud574 \ucc28\ub7c9\ub4e4\uc740 \uc548\uc804\ud558\uace0 \ud6a8\uc728\uc801\uc778 \uc8fc\ud589\uc774 \uac00\ub2a5\ud569\ub2c8\ub2e4.\n<\/p>\n
4.2 \uac8c\uc784 AI<\/h3>\n
\n \uac8c\uc784 \ubd84\uc57c\uc5d0\uc11c\ub3c4 \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc774 \ud65c\ubc1c\ud788 \ud65c\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\uc591\ud55c \uce90\ub9ad\ud130\uac00 \uc874\uc7ac\ud558\ub294 \uac8c\uc784\uc5d0\uc11c \uac01 \uce90\ub9ad\ud130\ub294 \uc0c1\ub300\ubc29\uc758 \uc804\ub7b5\uc744 \ud559\uc2b5\ud558\uace0 \uc774\uc5d0 \uc801\uc751\ud558\ub294 \ud615\ud0dc\ub85c \ud589\ub3d9\ud569\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \ub354\uc6b1 \ud604\uc2e4\uac10 \uc788\uace0 \ub3c4\uc804\uc801\uc778 \uac8c\uc784 \ud658\uacbd\uc744 \uc870\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n<\/p>\n
4.3 \ub85c\ubd07 \ud611\ub825<\/h3>\n
\n \uc5ec\ub7ec \ub300\uc758 \ub85c\ubd07\uc774 \ud611\ub825\ud558\uc5ec \ud2b9\uc815 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \uacbd\uc6b0, \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc744 \ud1b5\ud574 \ub85c\ubd07\ub4e4\uc774 \ud611\ub825\ud558\uc5ec \ubaa9\ud45c\ub97c \ub2ec\uc131\ud560 \uc218 \uc788\ub3c4\ub85d \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \ubb3c\uccb4 \uc6b4\ubc18, \uccad\uc18c, \uad6c\uc870 \ub4f1 \ub2e4\uc591\ud55c \uc791\uc5c5\uc5d0\uc11c \ub85c\ubd07 \uac04\uc758 \uc0c1\ud638\uc791\uc6a9\uc744 \ucd5c\uc801\ud654\ud558\ub294 \ub370 \ud65c\uc6a9\ub429\ub2c8\ub2e4.\n<\/p>\n
5. \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5 \uad6c\ud604 \uc608\uc81c<\/h2>\n
\n \uc544\ub798\ub294 OpenAI\uc758 Gym \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uac04\ub2e8\ud55c \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5 \ud658\uacbd\uc744 \uad6c\ud604\ud55c \uc608\uc81c\uc785\ub2c8\ub2e4. \uc774 \uc608\uc81c\uc5d0\uc11c\ub294 \ub450 \ub300\uc758 \uc5d0\uc774\uc804\ud2b8\uac00 \ud611\ub825\ud558\uc5ec \ubaa9\ud45c\ub97c \ub2ec\uc131\ud558\ub294 \uc0c1\ud669\uc744 \uc2dc\ubbac\ub808\uc774\uc158\ud569\ub2c8\ub2e4.\n<\/p>\n
\n\nimport gym\nimport numpy as np\n\nclass MultiAgentEnv:\n def __init__(self):\n self.agents = [0, 1] # \ub450 \uac1c\uc758 \uc5d0\uc774\uc804\ud2b8\n self.state = np.zeros((2, 4)) # \uac01 \uc5d0\uc774\uc804\ud2b8\uc758 \uc0c1\ud0dc\n self.goal = np.array([1, 1]) # \ubaa9\ud45c \uc0c1\ud0dc\n\n def reset(self):\n self.state = np.random.rand(2, 4) # \uc0c1\ud0dc \ucd08\uae30\ud654\n return self.state\n\n def step(self, actions):\n for i in range(len(self.agents)):\n self.state[i] += actions[i] # \uc5d0\uc774\uc804\ud2b8\uc758 \ud589\ub3d9\uc5d0 \ub530\ub77c \uc0c1\ud0dc \uc5c5\ub370\uc774\ud2b8\n reward = -np.linalg.norm(self.state - self.goal) # \ubaa9\ud45c\uc5d0 \uac00\uae4c\uc6cc\uc9c8\uc218\ub85d \ubcf4\uc0c1\n done = np.all(self.state == self.goal) # \ubaa9\ud45c\uc5d0 \ub3c4\ub2ec\ud588\ub294\uc9c0 \ud655\uc778\n return self.state, reward, done, {}\n\nenv = MultiAgentEnv()\nstate = env.reset()\n\nfor episode in range(5):\n done = False\n while not done:\n actions = [np.random.randn(4), np.random.randn(4)] # \uc784\uc758\uc758 \ud589\ub3d9 \uc120\ud0dd\n state, reward, done, _ = env.step(actions)\n print(f'\uc0c1\ud0dc: {state}, \ubcf4\uc0c1: {reward}')\n<\/code>\n<\/pre>\n6. \uacb0\ub860<\/h2>\n
\n \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc740 \ubcf5\uc7a1\ud55c \ub2e4\uc911 \ud658\uacbd\uc5d0\uc11c\uc758 \uc0c1\ud638\uc791\uc6a9\uc744 \ubaa8\ub378\ub9c1\ud558\uace0 \ud574\uacb0\ud558\ub294 \ub370 \uac15\ub825\ud55c \ub3c4\uad6c\uc785\ub2c8\ub2e4. \uc5d0\uc774\uc804\ud2b8\ub4e4\uc774 \ud611\ub825\ud558\uac70\ub098 \uacbd\uc7c1\ud558\ub294 \ub2e4\uc591\ud55c \uc0c1\ud669\uc744 \ud6a8\uacfc\uc801\uc73c\ub85c \ucc98\ub9ac\ud560 \uc218 \uc788\uc73c\uba70, \uc790\uc728\uc8fc\ud589\ucc28, \uac8c\uc784 AI, \ub85c\ubd07 \ud611\ub825 \ub4f1 \uc5ec\ub7ec \ubd84\uc57c\uc5d0\uc11c \uc2e4\uc81c\ub85c \ud65c\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc55e\uc73c\ub85c\ub3c4 \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc740 \ub354\uc6b1 \ubc1c\uc804\ud558\uc5ec \ub2e4\uc591\ud55c \ubb38\uc81c\ub97c \ud574\uacb0\ud558\ub294 \ub370 \uae30\uc5ec\ud560 \uac83\uc73c\ub85c \uae30\ub300\ub429\ub2c8\ub2e4.\n<\/p>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
\uac15\ud654\ud559\uc2b5(Reinforcement Learning, RL)\uc740 \uc5d0\uc774\uc804\ud2b8\uac00 \ud658\uacbd\uacfc \uc0c1\ud638\uc791\uc6a9\ud558\uba70 \ucd5c\ub300\uc758 \ubcf4\uc0c1\uc744 \uc5bb\uae30 \uc704\ud574 \ud559\uc2b5\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c \ub2e8\uc77c \uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5\uc740 \ud558\ub098\uc758 \uc5d0\uc774\uc804\ud2b8\uac00 \uc790\uc2e0\uc758 \uc815\ucc45\uc744 \ucd5c\uc801\ud654\ud558\uc5ec \ubaa9\ud45c\ub97c \ub2ec\uc131\ud558\ub294 \ubc29\ubc95\uc744 \ub2e4\ub8f9\ub2c8\ub2e4. \uadf8\ub7ec\ub098 \uc2e4\uc81c \uc138\uacc4\uc5d0\uc11c\ub294 \uc5ec\ub7ec \uc5d0\uc774\uc804\ud2b8\uac00 \uc874\uc7ac\ud558\ub294 \ud658\uacbd\uc5d0\uc11c\uc758 \uc0c1\ud638\uc791\uc6a9\uc774 \ube48\ubc88\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ud658\uacbd\uc744 \ub2e4\ub8e8\uae30 \uc704\ud574 \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5(Multi-Agent Reinforcement Learning, MARL)\uc774\ub77c\ub294 \uac1c\ub150\uc774 \ub4f1\uc7a5\ud588\uc2b5\ub2c8\ub2e4. \ubcf8 \uae00\uc5d0\uc11c\ub294 \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \ud658\uacbd\uc758 \uac1c\ub150\uacfc \uc774\ub97c \ud65c\uc6a9\ud558\uc5ec \uac15\ud654\ud559\uc2b5 \ubb38\uc81c\ub97c \ud574\uacb0\ud558\ub294 … \ub354 \ubcf4\uae30 “49. \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5(Multi-Agent RL) \uc774\ud574\ud558\uae30, \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \ud658\uacbd\uc758 \uac1c\ub150”<\/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-40402","post","type-post","status-publish","format-standard","hentry","category-213"],"yoast_head":"\n49. \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5(Multi-Agent RL) \uc774\ud574\ud558\uae30, \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \ud658\uacbd\uc758 \uac1c\ub150 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/40402\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"49. \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \uac15\ud654\ud559\uc2b5(Multi-Agent RL) \uc774\ud574\ud558\uae30, \uba40\ud2f0\uc5d0\uc774\uc804\ud2b8 \ud658\uacbd\uc758 \uac1c\ub150 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\uac15\ud654\ud559\uc2b5(Reinforcement Learning, RL)\uc740 \uc5d0\uc774\uc804\ud2b8\uac00 \ud658\uacbd\uacfc \uc0c1\ud638\uc791\uc6a9\ud558\uba70 \ucd5c\ub300\uc758 \ubcf4\uc0c1\uc744 \uc5bb\uae30 \uc704\ud574 \ud559\uc2b5\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4. 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\ub2e4\uc591\ud55c \uae30\ubc95\uc744 \ud1b5\ud574 \ub370\uc774\ud130\ub97c \ud559\uc2b5\ud558\uace0 \uc774\ub97c \uae30\ubc18\uc73c\ub85c \uc608\uce21 \ud639\uc740 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \uae30\uc220\uc774\ub2e4. \uadf8 \uc911\uc5d0\uc11c\ub3c4 \uac15\ud654\ud559\uc2b5\uc740 \uc5d0\uc774\uc804\ud2b8\uac00 \ud658\uacbd\uacfc \uc0c1\ud638\uc791\uc6a9\ud558\uba70 \ubcf4\uc0c1 \uc2e0\ud638\ub97c \ud1b5\ud574 \ud559\uc2b5\ud558\ub294 \ubc29\uc2dd\uc73c\ub85c, \ub2e4\ub978 \uba38\uc2e0\ub7ec\ub2dd \uae30\ubc95\ub4e4\uacfc\ub294 \ud655\uc5f0\ud788 \ub2e4\ub978 \ud2b9\uc9d5\uc744 \uac00\uc9c4\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \uac15\ud654\ud559\uc2b5\uacfc \ub2e4\ub978 \uba38\uc2e0\ub7ec\ub2dd \uae30\ubc95\ub4e4\uc744 \ube44\uad50\ud558\uace0, \uac15\ud654\ud559\uc2b5\uc758 \uc7a5\uc810\uacfc \ub2e8\uc810\uc744 \uc2ec\ub3c4 \uc788\uac8c\u2026","rel":"","context":""\uac15\ud654\ud559\uc2b5"\uc5d0\uc11c","block_context":{"text":"\uac15\ud654\ud559\uc2b5","link":"https:\/\/atmokpo.com\/w\/category\/%ea%b0%95%ed%99%94%ed%95%99%ec%8a%b5\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":40512,"url":"https:\/\/atmokpo.com\/w\/40512\/","url_meta":{"origin":40402,"position":2},"title":"54. \ubbf8\ub798\uc758 \uac15\ud654\ud559\uc2b5 \ucd5c\uc2e0 \uc5f0\uad6c \ub3d9\ud5a5\uacfc \ud5a5\ud6c4 \uc804\ub9dd, \uac15\ud654\ud559\uc2b5\uc758 \ubbf8\ub798 \uac00\ub2a5\uc131\uacfc \uc751\uc6a9 \ubd84\uc57c","author":"root","date":"2024\ub144 11\uc6d4 04\uc77c","format":false,"excerpt":"\uac15\ud654\ud559\uc2b5\uc740 \uc778\uacf5\uc9c0\ub2a5 \ubd84\uc57c\uc5d0\uc11c \uac00\uc7a5 \ud765\ubbf8\ub85c\uc6b4 \uc601\uc5ed \uc911 \ud558\ub098\ub85c, \uae30\uacc4 \ud559\uc2b5\uc758 \ud55c \ubd84\uc57c\ub85c\uc368, \uc5d0\uc774\uc804\ud2b8\uac00 \ud658\uacbd\uacfc \uc0c1\ud638\uc791\uc6a9\ud558\uba70 \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \ubc30\uc6b0\ub294 \uacfc\uc815\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4. \ubcf8 \uae00\uc5d0\uc11c\ub294 \uac15\ud654\ud559\uc2b5\uc758 \ucd5c\uc2e0 \uc5f0\uad6c \ub3d9\ud5a5\uacfc \uc804\ub9dd, \uadf8\ub9ac\uace0 \uc774 \uae30\uc220\uc774 \uc801\uc6a9\ub420 \uc218 \uc788\ub294 \ub2e4\uc591\ud55c \ubd84\uc57c\ub97c \uc2ec\uce35\uc801\uc73c\ub85c \ud0d0\uad6c\ud574\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uac15\ud654\ud559\uc2b5\uc758 \uac1c\uc694 \uac15\ud654\ud559\uc2b5\uc740 \uc5d0\uc774\uc804\ud2b8\uac00 \ud658\uacbd\uc5d0\uc11c\uc758 \uacbd\ud5d8\uc744 \ud1b5\ud574 \ubcf4\uc0c1\uc744 \ucd5c\ub300\ud654\ud558\ub294 \ubc29\ud5a5\uc73c\ub85c \ud589\ub3d9\uc744 \ud559\uc2b5\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4.\u2026","rel":"","context":""\uac15\ud654\ud559\uc2b5"\uc5d0\uc11c","block_context":{"text":"\uac15\ud654\ud559\uc2b5","link":"https:\/\/atmokpo.com\/w\/category\/%ea%b0%95%ed%99%94%ed%95%99%ec%8a%b5\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":40484,"url":"https:\/\/atmokpo.com\/w\/40484\/","url_meta":{"origin":40402,"position":3},"title":"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","author":"root","date":"2024\ub144 11\uc6d4 04\uc77c","format":false,"excerpt":"\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 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