\uc774 \uacfc\uc815\uc740 \uc5d0\uc774\uc804\ud2b8\uac00 \ucd5c\uc801\uc758 \uc815\ucc45\uc744 \ud559\uc2b5\ud560 \ub54c\uae4c\uc9c0 \uacc4\uc18d\ub429\ub2c8\ub2e4.<\/li>\n<\/ol>\n\uc608\uc2dc \uc18c\uc2a4 \ucf54\ub4dc<\/h2>\n
\n \ub2e4\uc74c\uc740 \ud30c\uc774\uc36c\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubbf8\ub85c\uc5d0\uc11c \uc5d0\uc774\uc804\ud2b8\uac00 \ubaa9\ud45c\uc9c0\uc810\uc5d0 \ub3c4\ub2ec\ud558\ub3c4\ub85d \uac15\ud654\ud559\uc2b5\uc744 \uc801\uc6a9\ud558\ub294 \uac04\ub2e8\ud55c \uc608\uc81c\uc785\ub2c8\ub2e4. \uc774 \uc608\uc81c\uc5d0\uc11c\ub294 Q-learning \uc54c\uace0\ub9ac\uc998\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc5d0\uc774\uc804\ud2b8\uac00 \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \ud559\uc2b5\ud569\ub2c8\ub2e4.\n<\/p>\n
import numpy as np\nimport random\n\n# \ubbf8\ub85c \ud658\uacbd \uc815\uc758\nclass Maze:\n def __init__(self, maze):\n self.maze = maze\n self.start = (0, 0)\n self.goal = (len(maze) - 1, len(maze[0]) - 1)\n self.state = self.start\n\n def reset(self):\n self.state = self.start\n return self.state\n\n def step(self, action):\n if action == 0: # \uc0c1\n new_state = (max(self.state[0] - 1, 0), self.state[1])\n elif action == 1: # \ud558\n new_state = (min(self.state[0] + 1, len(self.maze) - 1), self.state[1])\n elif action == 2: # \uc88c\n new_state = (self.state[0], max(self.state[1] - 1, 0))\n else: # \uc6b0\n new_state = (self.state[0], min(self.state[1] + 1, len(self.maze[0]) - 1))\n\n if self.maze[new_state[0]][new_state[1]] == 1: # \ubcbd\n return self.state, -1, False # \ubcf4\uc0c1\uc740 -1, \uc0c1\ud0dc \ubcc0\ud558\uc9c0 \uc54a\uc74c\n\n self.state = new_state\n\n if self.state == self.goal:\n return self.state, 10, True # \ubaa9\ud45c \ub3c4\ub2ec, \ubcf4\uc0c1 10\n\n return self.state, -1, False # \uc77c\ubc18\uc801\uc778 \uacbd\uc6b0, \ubcf4\uc0c1 -1\n\n# Q-learning \uc5d0\uc774\uc804\ud2b8 \uc815\uc758\nclass QLearningAgent:\n def __init__(self, actions, alpha=0.1, gamma=0.9, epsilon=0.1):\n self.q_table = {}\n self.actions = actions\n self.alpha = alpha\n self.gamma = gamma\n self.epsilon = epsilon\n\n def get_action(self, state):\n if state not in self.q_table:\n self.q_table[state] = np.zeros(len(self.actions))\n\n if random.random() < self.epsilon:\n return random.choice(self.actions) # \ub79c\ub364 \uc561\uc158 \uc120\ud0dd\n else:\n return np.argmax(self.q_table[state]) # \ucd5c\uc801 \uc561\uc158 \uc120\ud0dd\n\n def update(self, state, action, reward, next_state):\n if next_state not in self.q_table:\n self.q_table[next_state] = np.zeros(len(self.actions))\n\n # Q-\uac12 \uc5c5\ub370\uc774\ud2b8\n best_next_action = np.argmax(self.q_table[next_state])\n td_target = reward + self.gamma * self.q_table[next_state][best_next_action]\n self.q_table[state][action] += self.alpha * (td_target - self.q_table[state][action])\n\n\nif __name__ == '__main__':\n # \ubbf8\ub85c \uc815\uc758 (0: \ud1b5\ub85c, 1: \ubcbd)\n maze = [\n [0, 0, 1, 0],\n [1, 0, 1, 0],\n [0, 0, 0, 0],\n [0, 1, 1, 0],\n ]\n env = Maze(maze)\n agent = QLearningAgent(actions=[0, 1, 2, 3]) # \uc0c1, \ud558, \uc88c, \uc6b0\n\n episodes = 1000\n for episode in range(episodes):\n state = env.reset()\n done = False\n\n while not done:\n action = agent.get_action(state)\n next_state, reward, done = env.step(action)\n agent.update(state, action, reward, next_state)\n state = next_state\n\n # Q-\ud14c\uc774\ube14 \ucd9c\ub825\n for state, q_values in agent.q_table.items():\n print(f\"\uc0c1\ud0dc: {state}, Q-\uac12: {q_values}\")\n<\/code><\/pre>\n\uacb0\ub860<\/h2>\n
\n \uac15\ud654\ud559\uc2b5\uc740 \uc5d0\uc774\uc804\ud2b8\uc640 \ud658\uacbd \uac04\uc758 \uc0c1\ud638\uc791\uc6a9\uc744 \ud1b5\ud574 \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \ud559\uc2b5\ud558\ub294 \uac15\ub825\ud55c \uae30\ubc95\uc785\ub2c8\ub2e4. \uc5d0\uc774\uc804\ud2b8\ub294 \ubcf4\uc0c1\uc744 \ucd5c\ub300\ud654\ud558\uae30 \uc704\ud574 \ud589\ub3d9\uc744 \uc870\uc815\ud558\uba70, \uc774 \uacfc\uc815\uc5d0\uc11c \ub2e4\uc591\ud55c \uc54c\uace0\ub9ac\uc998\uacfc \uae30\uc220\uc774 \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \ubcf8 \uae00\uc5d0\uc11c\ub294 \uac15\ud654\ud559\uc2b5\uc758 \uc8fc\uc694 \uc6a9\uc5b4\uc640 \uad6c\uc131 \uc694\uc18c\uc5d0 \ub300\ud574 \uc0b4\ud3b4\ubcf4\uc558\uc73c\uba70, \ub610\ud55c \uac04\ub2e8\ud55c Q-learning \uc608\uc81c\ub97c \ud1b5\ud574 \uc774\ub97c \uc774\ud574\ud558\ub294 \ub370 \ub3c4\uc6c0\uc774 \ub418\uc5c8\uae30\ub97c \ubc14\ub78d\ub2c8\ub2e4.\n<\/p>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
\uac15\ud654\ud559\uc2b5(Reinforcement Learning, RL)\uc740 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud55c \ubd84\uc57c\ub85c, \uc5d0\uc774\uc804\ud2b8\uac00 \ud658\uacbd\uacfc \uc0c1\ud638\uc791\uc6a9\ud558\uc5ec \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \ud559\uc2b5\ud558\ub3c4\ub85d \ud558\ub294 \ubc29\ubc95\ub860\uc785\ub2c8\ub2e4. \uac15\ud654\ud559\uc2b5\uc740 \uc8fc\uc5b4\uc9c4 \uc0c1\ud0dc\uc5d0\uc11c \ud2b9\uc815 \ud589\ub3d9\uc744 \uc120\ud0dd\ud558\uace0, \uadf8 \ud589\ub3d9\uc5d0 \ub300\ud55c \ubcf4\uc0c1\uc744 \ubc1b\uace0, \uc774\ud6c4\uc758 \uc120\ud0dd\uc5d0 \ubc18\uc601\ud574 \ub098\uac00\ub294 iterative\ud55c \uacfc\uc815\uc73c\ub85c \uc791\ub3d9\ud569\ub2c8\ub2e4. \uac15\ud654\ud559\uc2b5\uc758 \ud575\uc2ec\uc740 \ub204\uc801 \ubcf4\uc0c1\uc744 \uadf9\ub300\ud654\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. \uac15\ud654\ud559\uc2b5\uc758 \uae30\ubcf8 \uad6c\uc131 \uc694\uc18c \uac15\ud654\ud559\uc2b5 \uc2dc\uc2a4\ud15c\uc740 \uc8fc\ub85c \ub2e4\uc74c\uacfc \uac19\uc740 \uad6c\uc131 \uc694\uc18c\ub85c \uc774\ub8e8\uc5b4\uc838 \uc788\uc2b5\ub2c8\ub2e4: \uc5d0\uc774\uc804\ud2b8 (Agent): \ud559\uc2b5\uc744 \uc218\ud589\ud558\uace0 … \ub354 \ubcf4\uae30 “2. \uac15\ud654\ud559\uc2b5\uc774\ub780 \ubb34\uc5c7\uc778\uac00 , \uc8fc\uc694 \uc6a9\uc5b4 \uc124\uba85 (\uc5d0\uc774\uc804\ud2b8, \ud658\uacbd, \uc0c1\ud0dc, \ud589\ub3d9, \ubcf4\uc0c1 \ub4f1)”<\/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-40508","post","type-post","status-publish","format-standard","hentry","category-213"],"yoast_head":"\n2. \uac15\ud654\ud559\uc2b5\uc774\ub780 \ubb34\uc5c7\uc778\uac00 , \uc8fc\uc694 \uc6a9\uc5b4 \uc124\uba85 (\uc5d0\uc774\uc804\ud2b8, \ud658\uacbd, \uc0c1\ud0dc, \ud589\ub3d9, \ubcf4\uc0c1 \ub4f1) - \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\/40508\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"2. \uac15\ud654\ud559\uc2b5\uc774\ub780 \ubb34\uc5c7\uc778\uac00 , \uc8fc\uc694 \uc6a9\uc5b4 \uc124\uba85 (\uc5d0\uc774\uc804\ud2b8, \ud658\uacbd, \uc0c1\ud0dc, \ud589\ub3d9, \ubcf4\uc0c1 \ub4f1) - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\uac15\ud654\ud559\uc2b5(Reinforcement Learning, RL)\uc740 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud55c \ubd84\uc57c\ub85c, \uc5d0\uc774\uc804\ud2b8\uac00 \ud658\uacbd\uacfc \uc0c1\ud638\uc791\uc6a9\ud558\uc5ec \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \ud559\uc2b5\ud558\ub3c4\ub85d \ud558\ub294 \ubc29\ubc95\ub860\uc785\ub2c8\ub2e4. \uac15\ud654\ud559\uc2b5\uc740 \uc8fc\uc5b4\uc9c4 \uc0c1\ud0dc\uc5d0\uc11c \ud2b9\uc815 \ud589\ub3d9\uc744 \uc120\ud0dd\ud558\uace0, \uadf8 \ud589\ub3d9\uc5d0 \ub300\ud55c \ubcf4\uc0c1\uc744 \ubc1b\uace0, \uc774\ud6c4\uc758 \uc120\ud0dd\uc5d0 \ubc18\uc601\ud574 \ub098\uac00\ub294 iterative\ud55c \uacfc\uc815\uc73c\ub85c \uc791\ub3d9\ud569\ub2c8\ub2e4. \uac15\ud654\ud559\uc2b5\uc758 \ud575\uc2ec\uc740 \ub204\uc801 \ubcf4\uc0c1\uc744 \uadf9\ub300\ud654\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. \uac15\ud654\ud559\uc2b5\uc758 \uae30\ubcf8 \uad6c\uc131 \uc694\uc18c \uac15\ud654\ud559\uc2b5 \uc2dc\uc2a4\ud15c\uc740 \uc8fc\ub85c \ub2e4\uc74c\uacfc \uac19\uc740 \uad6c\uc131 \uc694\uc18c\ub85c \uc774\ub8e8\uc5b4\uc838 \uc788\uc2b5\ub2c8\ub2e4: \uc5d0\uc774\uc804\ud2b8 (Agent): \ud559\uc2b5\uc744 \uc218\ud589\ud558\uace0 … \ub354 \ubcf4\uae30 "2. \uac15\ud654\ud559\uc2b5\uc774\ub780 \ubb34\uc5c7\uc778\uac00 , \uc8fc\uc694 \uc6a9\uc5b4 \uc124\uba85 (\uc5d0\uc774\uc804\ud2b8, \ud658\uacbd, \uc0c1\ud0dc, \ud589\ub3d9, \ubcf4\uc0c1 \ub4f1)"\" \/>\n<meta property=\"og:url\" content=\"https:\/\/atmokpo.com\/w\/40508\/\" \/>\n<meta property=\"og:site_name\" content=\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"article:published_time\" content=\"2024-11-04T01:52:19+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-26T06:39:00+00:00\" \/>\n<meta name=\"author\" content=\"root\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:site\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:label1\" content=\"\uae00\uc4f4\uc774\" \/>\n\t<meta name=\"twitter:data1\" content=\"root\" \/>\n\t<meta name=\"twitter:label2\" content=\"\uc608\uc0c1 \ub418\ub294 \ud310\ub3c5 \uc2dc\uac04\" \/>\n\t<meta name=\"twitter:data2\" content=\"2\ubd84\" \/>\n<script type=\"application\/ld+json\" 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\ub4f1)\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/atmokpo.com\/w\/#website\",\"url\":\"https:\/\/atmokpo.com\/w\/\",\"name\":\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/atmokpo.com\/w\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/atmokpo.com\/w\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"ko-KR\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/atmokpo.com\/w\/#organization\",\"name\":\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\",\"url\":\"https:\/\/atmokpo.com\/w\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ko-KR\",\"@id\":\"https:\/\/atmokpo.com\/w\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/11\/logo.png\",\"contentUrl\":\"https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/11\/logo.png\",\"width\":400,\"height\":400,\"caption\":\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\"},\"image\":{\"@id\":\"https:\/\/atmokpo.com\/w\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/x.com\/bebubo4\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/atmokpo.com\/w\/#\/schema\/person\/91b6b3b138fbba0efb4ae64b1abd81d7\",\"name\":\"root\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ko-KR\",\"@id\":\"https:\/\/atmokpo.com\/w\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/708197b41fc6435a7ce22d951b25d4a47e9e904270cb1f04682d4f025066f80c?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/708197b41fc6435a7ce22d951b25d4a47e9e904270cb1f04682d4f025066f80c?s=96&d=mm&r=g\",\"caption\":\"root\"},\"sameAs\":[\"http:\/\/atmokpo.com\/w\"],\"url\":\"https:\/\/atmokpo.com\/w\/author\/root\/\"}]}<\/script>\n<!-- 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