{"id":40450,"date":"2024-11-04T01:51:50","date_gmt":"2024-11-04T01:51:50","guid":{"rendered":"https:\/\/atmokpo.com\/w\/?p=40450"},"modified":"2024-11-26T06:39:09","modified_gmt":"2024-11-26T06:39:09","slug":"45-%ea%b0%95%ed%99%94%ed%95%99%ec%8a%b5%ec%9d%98-%ed%95%9c%ea%b3%84%ec%99%80-%eb%8f%84%ec%a0%84-%ea%b3%bc%ec%a0%9c-%ec%83%81%ed%83%9c-%eb%b0%8f-%ed%96%89%eb%8f%99-%ea%b3%b5%ea%b0%84%ec%9d%98","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/40450\/","title":{"rendered":"45. \uac15\ud654\ud559\uc2b5\uc758 \ud55c\uacc4\uc640 \ub3c4\uc804 \uacfc\uc81c, \uc0c1\ud0dc \ubc0f \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30"},"content":{"rendered":"

<\/p>\n

\uac15\ud654\ud559\uc2b5(Reinforcement Learning, RL)\uc740 \uc5d0\uc774\uc804\ud2b8(Agent)\uac00 \ud658\uacbd(Environment)\uacfc \uc0c1\ud638\uc791\uc6a9\ud558\uba70 \ucd5c\uc801\uc758 \ud589\ub3d9 \uc815\ucc45(Policy)\uc744 \ud559\uc2b5\ud558\ub294 \uae30\uacc4 \ud559\uc2b5\uc758 \ud55c \ubd84\uc57c\uc774\ub2e4. \ucd5c\uadfc \uba87 \ub144\uac04 \uac15\ud654\ud559\uc2b5\uc740 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ub192\uc740 \uc131\uacfc\ub97c \ubcf4\uc5ec\uc8fc\uc5c8\uc73c\ub098, \uc544\uc9c1\ub3c4 \ud574\uacb0\ud574\uc57c \ud560 \ub9ce\uc740 \ud55c\uacc4\uc640 \ub3c4\uc804 \uacfc\uc81c\uac00 \uc874\uc7ac\ud55c\ub2e4. \uadf8\uc911\uc5d0\uc11c\ub3c4 \uc0c1\ud0dc \ubc0f \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30\ub294 \uac15\ud654\ud559\uc2b5\uc758 \uc131\ub2a5\uacfc \ud6a8\uc728\uc131\uc5d0 \ud070 \uc601\ud5a5\uc744 \ubbf8\uce5c\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \uac15\ud654\ud559\uc2b5\uc758 \ud55c\uacc4\uc640 \ub3c4\uc804 \uacfc\uc81c\ub97c \uc18c\uac1c\ud558\uace0, \uc0c1\ud0dc \ubc0f \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30\uac00 \uac00\uc9c0\ub294 \uc758\ubbf8\uc640 \uc774\ub85c \uc778\ud574 \ubc1c\uc0dd\ud560 \uc218 \uc788\ub294 \ubb38\uc81c\uc5d0 \ub300\ud574 \uae4a\uc774 \uc788\ub294 \ubd84\uc11d\uc744 \uc9c4\ud589\ud558\uace0\uc790 \ud55c\ub2e4.<\/p>\n

1. \uac15\ud654\ud559\uc2b5\uc758 \uae30\ubcf8 \uac1c\ub150<\/h2>\n

\uac15\ud654\ud559\uc2b5\uc740 \uc5d0\uc774\uc804\ud2b8\uac00 \ud658\uacbd\uacfc\uc758 \uc0c1\ud638\uc791\uc6a9\uc744 \ud1b5\ud574 \ubcf4\uc0c1(Reward)\uc744 \ucd5c\ub300\ud654\ud558\ub294 \ubc29\ud5a5\uc73c\ub85c \ud559\uc2b5\ud558\ub294 \uc54c\uace0\ub9ac\uc998\uc774\ub2e4. \uc5d0\uc774\uc804\ud2b8\ub294 \uc8fc\uc5b4\uc9c4 \uc0c1\ud0dc(State)\uc5d0\uc11c \ud589\ub3d9(Action)\uc744 \uc120\ud0dd\ud558\uace0, \uadf8 \uacb0\uacfc\ub85c \ud658\uacbd\uc774 \uc5b4\ub5bb\uac8c \ubcc0\ud654\ud558\uba70 \uc5b4\ub5a4 \ubcf4\uc0c1\uc744 \ubc1b\ub294\uc9c0\ub97c \uacbd\ud5d8\ud558\uc5ec \ucd5c\uc801\uc758 \uc815\ucc45\uc744 \ud559\uc2b5\ud55c\ub2e4.<\/p>\n

1.1. \uc0c1\ud0dc(S)\uc640 \ud589\ub3d9(A) \uacf5\uac04<\/h3>\n

\uc0c1\ud0dc \uacf5\uac04\uc740 \ud658\uacbd\uc758 \ubaa8\ub4e0 \uac00\ub2a5\ud55c \uc0c1\ud0dc\ub97c \ub098\ud0c0\ub0b4\uba70, \ud589\ub3d9 \uacf5\uac04\uc740 \uc5d0\uc774\uc804\ud2b8\uac00 \uc120\ud0dd\ud560 \uc218 \uc788\ub294 \ubaa8\ub4e0 \uac00\ub2a5\ud55c \ud589\ub3d9\uc744 \ub098\ud0c0\ub0b8\ub2e4. \uac04\ub2e8\ud55c \uc608\ub85c, \uccb4\uc2a4 \uac8c\uc784\uc744 \uc0dd\uac01\ud574\ubcf4\uba74, \uc0c1\ud0dc \uacf5\uac04\uc740 \uccb4\uc2a4\ud310\uc758 \ubaa8\ub4e0 \uac00\ub2a5\ud55c \ubc30\uce58(\uac01 \uae30\ubb3c\uc758 \uc704\uce58)\uc774\uba70, \ud589\ub3d9 \uacf5\uac04\uc740 \uac00\ub2a5\ud55c \ubaa8\ub4e0 \uc218\ub97c \uc758\ubbf8\ud55c\ub2e4.<\/p>\n

2. \uac15\ud654\ud559\uc2b5\uc758 \ud55c\uacc4<\/h2>\n

\uac15\ud654\ud559\uc2b5\uc740 \ub9e4\uc6b0 \uac15\ub825\ud55c \ub3c4\uad6c\uc9c0\ub9cc, \uba87 \uac00\uc9c0 \uc911\uc694\ud55c \ud55c\uacc4\uac00 \uc788\ub2e4.<\/p>\n

2.1. \ucc28\uc6d0 \ubb38\uc81c(Curse of Dimensionality)<\/h3>\n

\uc0c1\ud0dc \ubc0f \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30\uac00 \ucee4\uc9c8\uc218\ub85d Q-\ub7ec\ub2dd(Q-learning)\uacfc \uac19\uc740 \uc804\ud1b5\uc801\uc778 \uac15\ud654\ud559\uc2b5 \uc54c\uace0\ub9ac\uc998\uc758 \uc131\ub2a5\uc774 \ud604\uc800\ud788 \uc800\ud558\ub41c\ub2e4. \uc774\ub97c \ucc28\uc6d0 \ubb38\uc81c\ub77c\uace0 \ud558\uba70, \uc0c1\ud0dc\uc640 \ud589\ub3d9\uc758 \uc870\ud569\uc774 \uae30\ud558\uae09\uc218\uc801\uc73c\ub85c \ub298\uc5b4\ub0a8\uc5d0 \ub530\ub77c \ud0d0\uc0c9 \uacf5\uac04\uc774 \ucee4\uc9c0\uace0, \uacb0\uad6d\uc5d0\ub294 \uc5d0\uc774\uc804\ud2b8\uac00 \uc720\uc758\ubbf8\ud55c \uc815\ucc45\uc744 \ud559\uc2b5\ud560 \uc218 \uc5c6\uac8c \ub41c\ub2e4.<\/p>\n

2.2. \uc0d8\ud50c \ud6a8\uc728\uc131(Sample Efficiency)<\/h3>\n

\uac15\ud654\ud559\uc2b5\uc5d0\uc11c\ub294 \uc5d0\uc774\uc804\ud2b8\uac00 \uacbd\ud5d8\uc744 \ud1b5\ud574 \uc815\ucc45\uc744 \uc5c5\ub370\uc774\ud2b8\ud55c\ub2e4. \ud558\uc9c0\ub9cc \uc774\ub7ec\ud55c \uc5c5\ub370\uc774\ud2b8\ub97c \uc704\ud574 \uc77c\uc815\ub7c9\uc758 \uacbd\ud5d8\uc774 \ud544\uc694\ud558\uba70, \uc774 \uacbd\ud5d8\uc774 \ubd80\uc871\ud560 \uacbd\uc6b0 \uc131\ub2a5\uc774 \uc800\ud558\ub41c\ub2e4. \ud2b9\ud788 \ubcf5\uc7a1\ud55c \ud658\uacbd\uc5d0\uc11c \ucda9\ubd84\ud55c \uacbd\ud5d8\uc744 \ucd95\uc801\ud558\ub294 \uac83\uc740 \uc2dc\uac04\uc774 \ub9ce\uc774 \uc18c\uc694\ub418\uba70, \uc5d0\uc774\uc804\ud2b8\uac00 \ud0d0\uc0c9\ud558\ub294 \ub370 \ub4dc\ub294 \ube44\uc6a9\uc774 \ube44\uc300 \uc218 \uc788\ub2e4.<\/p>\n

2.3. \ube44\uac00\uc5ed\uc801 \ud559\uc2b5(Irreversible Learning)<\/h3>\n

\uac15\ud654\ud559\uc2b5\uc5d0\uc11c\ub294 \uc798\ubabb\ub41c \ud589\ub3d9\uc744 \uc120\ud0dd\ud588\uc744 \uacbd\uc6b0, \ud658\uacbd\uc73c\ub85c\ubd80\ud130 \ubc1b\uc740 \ubd80\uc815\uc801\uc778 \ubcf4\uc0c1\uc73c\ub85c \uc778\ud574 \ube60\ub974\uac8c \uac00\uce58 \ud568\uc218\ub97c \uc5c5\ub370\uc774\ud2b8\ud560 \uc218 \uc788\ub2e4. \ud558\uc9c0\ub9cc \uc774\ub7ec\ud55c \uc5c5\ub370\uc774\ud2b8\uac00 \uc798\ubabb\ub41c \ubc29\ud5a5\uc73c\ub85c \uc9c4\ud589\ub420 \uc218 \uc788\uc73c\uba70, \uc5d0\uc774\uc804\ud2b8\ub294 \uc798\ubabb\ub41c \uacbd\ub85c\uc5d0 \ube60\uc9c8 \uc704\ud5d8\uc774 \ud06c\ub2e4.<\/p>\n

3. \uc0c1\ud0dc \ubc0f \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30<\/h2>\n

\uc0c1\ud0dc \ubc0f \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30\ub294 \uac15\ud654\ud559\uc2b5\uc5d0\uc11c \uac00\uc7a5 \uc911\uc694\ud55c \uc694\uc18c \uc911 \ud558\ub098\uc774\ub2e4. \uc774\ub294 \uc5d0\uc774\uc804\ud2b8\uc758 \ud559\uc2b5\uc774 \uac00\ub2a5\ud55c \ubc94\uc704\ub97c \uc815\uc758\ud558\uba70, \ud0d0\uc0c9 \ud6a8\uc728\uc131\uacfc \uad00\ub828\uc774 \uc788\ub2e4.<\/p>\n

3.1. \uc0c1\ud0dc \uacf5\uac04\uc758 \ud06c\uae30<\/h3>\n

\uc0c1\ud0dc \uacf5\uac04\uc758 \ud06c\uae30\uac00 \ud06c\uba74, \uc5d0\uc774\uc804\ud2b8\uac00 \ud2b9\uc815\ud55c \uc0c1\ud0dc\uc5d0\uc11c \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \ucc3e\uae30 \uc704\ud574 \ud544\uc694\ud55c \ud559\uc2b5 \uc2dc\uac04\uc774 \uc99d\uac00\ud55c\ub2e4. \uc774\ub294 \uc5d0\uc774\uc804\ud2b8\uac00 \ud6c8\ub828\ubc1b\ub294 \ub370\uc774\ud130\uc758 \uc591\uc774 \uae30\ud558\uae09\uc218\uc801\uc73c\ub85c \uc99d\uac00\ud558\uba70, \uc2e4\uc81c\ub85c\ub294 \ubaa8\ub4e0 \uc0c1\ud0dc\ub97c \ud0d0\uc0c9\ud560 \uc218 \uc5c6\ub294 \uacbd\uc6b0\uac00 \ub9ce\ub2e4.<\/p>\n

3.2. \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30<\/h3>\n

\ud589\ub3d9 \uacf5\uac04\uc774 \ud06c\uba74, \uac01 \uc0c1\ud0dc\uc5d0\uc11c \uc120\ud0dd\ud560 \uc218 \uc788\ub294 \ud6c4\ubcf4 \ud589\ub3d9\uc774 \ub9ce\uc544\uc838 \uc5d0\uc774\uc804\ud2b8\ub294 \ub354 \ubcf5\uc7a1\ud55c \uc815\ucc45\uc744 \ud559\uc2b5\ud574\uc57c \ud55c\ub2e4. \uc774\ub7ec\ud55c \uacbd\uc6b0\uc5d0\ub294 \uae30\uc874\uc758 \uac15\ud654\ud559\uc2b5 \ubc29\ubc95\uc73c\ub85c\ub294 \ube44\ud6a8\uc728\uc801\uc778 \ud0d0\uc0c9\uc774 \uc774\ub8e8\uc5b4\uc9c8 \uc218 \uc788\uc73c\uba70, \ucd5c\uc801\uc758 \uc815\ucc45\uc744 \ucc3e\uae30 \uc5b4\ub824\uc6b8 \uc218 \uc788\ub2e4.<\/p>\n

4. \ud574\uacb0 \ubc29\uc548\uacfc \ub3c4\uc804 \uacfc\uc81c<\/h2>\n

\uc0c1\ud0dc \ubc0f \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30\uc5d0 \uc758\ud574 \ubc1c\uc0dd\ud558\ub294 \ubb38\uc81c\ub97c \ud574\uacb0\ud558\uae30 \uc704\ud574 \uc5ec\ub7ec \uac00\uc9c0 \uc811\uadfc \ubc29\uc2dd\uc774 \ud544\uc694\ud558\ub2e4. \ub2e4\uc74c\uc740 \uadf8 \uc911 \uc77c\ubd80\uc774\ub2e4.<\/p>\n

4.1. \ud568\uc218 \uadfc\uc0ac(Function Approximation)<\/h3>\n

\uc0c1\ud0dc \ubc0f \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30\ub97c \uc904\uc774\uae30 \uc704\ud55c \ud6a8\uacfc\uc801\uc778 \ubc29\ubc95 \uc911 \ud558\ub098\ub294 \ud568\uc218 \uadfc\uc0ac\ub97c \ud65c\uc6a9\ud558\uc5ec Q-\uac12\uc774\ub098 \uc815\ucc45 \ud568\uc218\ub97c \uadfc\uc0ac\ud558\ub294 \uac83\uc774\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc778\uacf5 \uc2e0\uacbd\ub9dd\uc744 \uc0ac\uc6a9\ud558\uc5ec Q-\uac12\uc744 \uc608\uce21\ud568\uc73c\ub85c\uc368 \ub192\uc740 \ucc28\uc6d0 \ubb38\uc81c\ub97c \ud574\uacb0\ud560 \uc218 \uc788\ub2e4.<\/p>\n

4.2. \uacc4\uce35\uc801 \uac15\ud654\ud559\uc2b5(Hierarchical Reinforcement Learning)<\/h3>\n

\uacc4\uce35\uc801 \uac15\ud654\ud559\uc2b5\uc740 \ubcf5\uc7a1\ud55c \uc791\uc5c5\uc744 \ub354 \uac04\ub2e8\ud55c \ud558\uc704 \uc791\uc5c5\uc73c\ub85c \ub098\ub204\ub294 \uc811\uadfc \ubc29\uc2dd\uc774\ub2e4. \uc774\ub97c \ud1b5\ud574 \uc5d0\uc774\uc804\ud2b8\ub294 \uac01 \ud558\uc704 \uc791\uc5c5\uc5d0 \ub300\ud55c \uc815\ucc45\uc744 \ud559\uc2b5\ud558\uace0, \uc774\ub97c \uc870\ud569\ud558\uc5ec \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \uc218\ud589\ud560 \uc218 \uc788\ub2e4.<\/p>\n

4.3. \uc801\ub300\uc801 \ud559\uc2b5(Adversarial Training)<\/h3>\n

\uc801\ub300\uc801 \ud559\uc2b5\uc740 \uac15\ud654\ud559\uc2b5 \uc5d0\uc774\uc804\ud2b8\uc758 \uc131\ub2a5\uc744 \uac1c\uc120\ud558\uae30 \uc704\ud574 \uacbd\uc7c1\uc790\ub97c \ub3c4\uc785\ud558\ub294 \ubc29\ubc95\uc774\ub2e4. \uc774\ub97c \ud1b5\ud574 \uc5d0\uc774\uc804\ud2b8\ub294 \ub354 \ub2e4\uc591\ud55c \uc0c1\ud669\uc5d0\uc11c \ud559\uc2b5\ud560 \uc218 \uc788\uc73c\uba70, \uc548\uc815\uc131\uc744 \ud06c\uac8c \ud5a5\uc0c1\uc2dc\ud0ac \uc218 \uc788\ub2e4.<\/p>\n

5. \uc608\uc81c \uc18c\uc2a4 \ucf54\ub4dc<\/h2>\n

\ub2e4\uc74c\uc740 OpenAI\uc758 Gym \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec \uac04\ub2e8\ud55c \uac15\ud654\ud559\uc2b5 \ud658\uacbd\uc744 \uad6c\ucd95\ud558\uace0, Q-\ub7ec\ub2dd\uc744 \ud1b5\ud55c \uc5d0\uc774\uc804\ud2b8 \ud559\uc2b5\uc744 \uad6c\ud604\ud558\ub294 \uc608\uc81c \ucf54\ub4dc\uc774\ub2e4.<\/p>\n

\n        \nimport numpy as np\nimport gym\n\n# Q-\ud14c\uc774\ube14 \ucd08\uae30\ud654\ndef create_q_table(state_size, action_size):\n    return np.zeros((state_size, action_size))\n\n# Q-\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\ndef q_learning(env, num_episodes, alpha, gamma, epsilon):\n    q_table = create_q_table(env.observation_space.n, env.action_space.n)\n    for episode in range(num_episodes):\n        state = env.reset()\n        done = False\n\n        while not done:\n            # \uc5d0\uc774\uc804\ud2b8\uc758 \ud589\ub3d9 \uc120\ud0dd\n            if np.random.rand() < epsilon:\n                action = env.action_space.sample()  # \ub79c\ub364 \ud589\ub3d9\n            else:\n                action = np.argmax(q_table[state])  # \ucd5c\uc801 \ud589\ub3d9 \uc120\ud0dd\n\n            next_state, reward, done, _ = env.step(action)\n            old_value = q_table[state, action]\n            next_max = np.max(q_table[next_state])\n\n            # Q-\uac12 \uc5c5\ub370\uc774\ud2b8\n            q_table[state, action] = (1 - alpha) * old_value + alpha * (reward + gamma * next_max)\n\n            state = next_state\n\n    return q_table\n\n# \ud658\uacbd \uc124\uc815\nenv = gym.make('Taxi-v3')\nq_table = q_learning(env, num_episodes=10000, alpha=0.1, gamma=0.6, epsilon=0.1)\n\n# \ud559\uc2b5 \uacb0\uacfc \ucd9c\ub825\nprint(\"\ud6c8\ub828\ub41c Q-\ud14c\uc774\ube14:\")\nprint(q_table)\n        <\/code>\n    <\/pre>\n
6. \uacb0\ub860<\/h2>\n
\uac15\ud654\ud559\uc2b5\uc740 \ub9e4\uc6b0 \uac15\ub825\ud55c \uae30\uacc4 \ud559\uc2b5 \ubc29\ubc95\uc774\uc9c0\ub9cc, \uc0c1\ud0dc \ubc0f \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30\uac00 \ud55c\uacc4\uc640 \ub3c4\uc804 \uacfc\uc81c\uac00 \ub420 \uc218 \uc788\ub2e4. \uc774\ub97c \ud574\uacb0\ud558\uae30 \uc704\ud55c \ub2e4\uc591\ud55c \ubc29\ubc95\ub4e4\uc774 \uc81c\uc548\ub418\uace0 \uc788\uc73c\uba70, \uc55e\uc73c\ub85c\ub3c4 \ub9ce\uc740 \uc5f0\uad6c\uac00 \ud544\uc694\ud560 \uac83\uc774\ub2e4. \ubcf8 \uae00\uc5d0\uc11c\ub294 \uac15\ud654\ud559\uc2b5\uc758 \uae30\ubcf8 \uac1c\ub150\uacfc \ud55c\uacc4, \uc0c1\ud0dc \ubc0f \ud589\ub3d9 \uacf5\uac04\uc758 \ud06c\uae30, \ud574\uacb0 \ubc29\uc548 \ub4f1\uc744 \uc54c\uc544\ubcf4\uc558\ub2e4. \uc774\ub7ec\ud55c \uc8fc\uc81c\ub97c \ubc14\ud0d5\uc73c\ub85c \uae4a\uc774 \uc788\ub294 \ud0d0\uad6c\ub97c \uc774\uc5b4\uac00\uae38 \ubc14\ub780\ub2e4.<\/p>\n
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