\uc791\uc5c5\uc758 \ubaa9\ud45c \uc9c0\uc810\uc5d0 \uac00\uae4c\uc6cc\uc9c8\uc218\ub85d \uc810\uc9c4\uc801\uc73c\ub85c \uc99d\uac00\ud558\ub294 \ubcf4\uc0c1 \uc124\uacc4<\/li>\n<\/ul>\n2.2. \uacfc\ub3c4\ud55c \ubcf4\uc0c1\uacfc \ubc8c\uc810 \ud53c\ud558\uae30<\/h3>\n
\uc5d0\uc774\uc804\ud2b8\uac00 \ud6a8\uacfc\uc801\uc73c\ub85c \ud559\uc2b5\ud558\uae30 \uc704\ud574\uc11c\ub294 \uc9c0\ub098\uce58\uac8c \ud070 \ubcf4\uc0c1\uc774\ub098 \ubc8c\uc810\uc744 \ud53c\ud558\ub294 \uac83\uc774 \uc88b\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc0c1\ud669\uc740 \uc5d0\uc774\uc804\ud2b8\uac00 \ud2b9\uc815 \ud589\ub3d9\uc5d0 \ub300\ud574 \uacfc\ub3c4\ud55c \uc758\uc874\uc131\uc744 \uac00\uc9c8 \uc218 \uc788\ub3c4\ub85d \ub9cc\ub4e4\uba70, \uc774\ub294 \ud559\uc2b5\uc744 \uc800\ud574\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
2.3. \uc9c0\uc5f0 \ubcf4\uc0c1 \ucc98\ub9ac<\/h3>\n
\ub300\ubd80\ubd84\uc758 \ud658\uacbd\uc5d0\uc11c\ub294 \uc989\uac01\uc801\uc778 \ubcf4\uc0c1\ubcf4\ub2e4\ub294 \uc9c0\uc5f0 \ubcf4\uc0c1\uc774 \uc801\uc808\ud55c \uacbd\uc6b0\uac00 \ub9ce\uc2b5\ub2c8\ub2e4. \uc774\ub294 \uc5d0\uc774\uc804\ud2b8\uac00 \uc5ec\ub7ec \ud589\ub3d9\uc744 \uc5f0\uc18d\uc801\uc73c\ub85c \ucde8\ud55c \ud6c4\uc5d0\uc57c \ubcf4\uc0c1\uc744 \ubc1b\ub294 \uad6c\uc870\ub97c \uc758\ubbf8\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uacbd\uc6b0, \uc5d0\uc774\uc804\ud2b8\ub294 \ud589\ub3d9 \uac04\uc758 \uc5f0\uad00\uc131\uc744 \uba85\ud655\ud788 \uc774\ud574\ud560 \uc218 \uc788\ub3c4\ub85d \ubcf4\uc0c1\uc744 \uc124\uacc4\ud574\uc57c \ud569\ub2c8\ub2e4.<\/p>\n
2.4. \ubcf4\uc0c1\uc758 \ubc00\ub3c4 \ubc0f \ubcc0\ub3d9\uc131 \uac10\uc18c<\/h3>\n
\uc5d0\uc774\uc804\ud2b8\uac00 \ud559\uc2b5\ud560 \uc218 \uc788\ub294 \ud765\ubbf8\ub85c\uc6b4 \ubcf4\uc0c1\uc744 \uc81c\uacf5\ud558\ub418, \uc774\uc758 \ubcc0\ub3d9\uc131\uc744 \ucd5c\uc18c\ud654\ud574\uc57c \ud569\ub2c8\ub2e4. \ubd88\ud544\uc694\ud558\uac8c \ubcc0\ud654\uac00 \uc2ec\ud55c \ubcf4\uc0c1\uc740 \uc5d0\uc774\uc804\ud2b8\ub85c \ud558\uc5ec\uae08 \ud63c\ub780\uc5d0 \ube60\uc9c0\uac8c \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
2.5. \ubd80\uc218\uc801 \ud589\ub3d9 \uace0\ub824<\/h3>\n
\ubcf4\uc0c1 \ud568\uc218\ub97c \uc124\uacc4\ud560 \ub54c\ub294 \uc8fc \ubaa9\ud45c\ubfd0\ub9cc \uc544\ub2c8\ub77c \ubd80\uc218\uc801\uc778 \ud589\ub3d9\uc5d0 \ub300\ud574\uc11c\ub3c4 \ubcf4\uc0c1\uc744 \uace0\ub824\ud574\uc57c \ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc790\ub3d9\ucc28\ub97c \uc8fc\ud589\ud558\ub294 \uc5d0\uc774\uc804\ud2b8\ub77c\uba74, \uc8fc\ud589 \uacbd\ub85c\ub97c \ub530\ub974\ub294 \uac83\ubfd0\ub9cc \uc544\ub2c8\ub77c \uc2e0\ud638\ub97c \uc9c0\ud0a4\ub294 \uac83\uacfc \uac19\uc740 \ud589\ub3d9\uc5d0\ub3c4 \ubcf4\uc0c1\uc744 \ubd80\uc5ec\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
3. \ubcf4\uc0c1 \ud568\uc218 \uc124\uacc4 \uc608\uc2dc<\/h2>\n
\uc774\uc81c \ud2b9\uc815 \uc608\uc2dc\ub97c \ud1b5\ud574 \ubcf4\uc0c1 \ud568\uc218 \uc124\uacc4\ub97c \uad6c\uccb4\uc801\uc73c\ub85c \ub2e4\ub904\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uc544\ub798\uc758 \uc608\uc2dc\ub294 \uac04\ub2e8\ud55c \uadf8\ub9ac\ub4dc \uc6d4\ub4dc(Grid World) \ud658\uacbd\uc5d0\uc11c \uc5d0\uc774\uc804\ud2b8\uac00 \ubaa9\ud45c \uc9c0\uc810\uc5d0 \ub3c4\ub2ec\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud558\ub294 \uacbd\uc6b0\uc785\ub2c8\ub2e4.<\/p>\n
3.1. \uae30\ubcf8 \ud658\uacbd \uc124\uc815<\/h3>\n
\uba3c\uc800, \uadf8\ub9ac\ub4dc \uc6d4\ub4dc \ud658\uacbd\uc744 \uc124\uc815\ud558\uaca0\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc11c\ub294 5×5 \ud06c\uae30\uc758 \uaca9\uc790\uc5d0\uc11c \uc5d0\uc774\uc804\ud2b8\uac00 (0, 0) \uc704\uce58\uc5d0\uc11c \uc2dc\uc791\ud574 (4, 4) \uc704\uce58\ub85c \uc774\ub3d9\ud558\ub294 \uacbd\uc6b0\ub97c \uac00\uc815\ud569\ub2c8\ub2e4.<\/p>\n
import numpy as np\n\nclass GridWorld:\n def __init__(self):\n self.grid_size = 5\n self.state = (0, 0) # \uc5d0\uc774\uc804\ud2b8 \uc2dc\uc791 \uc704\uce58\n self.goal_state = (4, 4) # \ubaa9\ud45c \uc704\uce58\n self.action_space = [(0, 1), (1, 0), (0, -1), (-1, 0)] # \uc624\ub978\ucabd, \uc544\ub798, \uc67c\ucabd, \uc704\n\n def reset(self):\n self.state = (0, 0)\n return self.state\n\n def step(self, action):\n # \uc0c1\ud0dc \uc5c5\ub370\uc774\ud2b8\n next_state = (self.state[0] + action[0], self.state[1] + action[1])\n # \uacbd\uacc4 \uccb4\ud06c\n if 0 <= next_state[0] < self.grid_size and 0 <= next_state[1] < self.grid_size:\n self.state = next_state\n \n # \ubcf4\uc0c1 \ubc0f \uc885\ub8cc \ud655\uc778\n if self.state == self.goal_state:\n return self.state, 1, True # \ubaa9\ud45c \ub3c4\ub2ec \uc2dc \ubcf4\uc0c1 1\n else:\n return self.state, -0.1, False # \uc77c\ubc18 \uc774\ub3d9 \uc2dc \uc18c\ub7c9\uc758 \uc74c\uc758 \ubcf4\uc0c1\n<\/code><\/pre>\n3.2. \uc5d0\uc774\uc804\ud2b8 \ud559\uc2b5<\/h3>\n
\ub2e4\uc74c\uc73c\ub85c, \uc704\uc758 \ud658\uacbd\uc744 \uc774\uc6a9\ud574 \uac04\ub2e8\ud55c Q-\ub7ec\ub2dd \uc5d0\uc774\uc804\ud2b8\ub97c \uad6c\ud604\ud558\uaca0\uc2b5\ub2c8\ub2e4. \uc5d0\uc774\uc804\ud2b8\ub294 \ubcf4\uc0c1 \ud568\uc218\ub97c \ud1b5\ud574 \ud559\uc2b5\ud569\ub2c8\ub2e4.<\/p>\n
class QLearningAgent:\n def __init__(self, environment):\n self.env = environment\n self.q_table = np.zeros((environment.grid_size, environment.grid_size, len(environment.action_space)))\n self.alpha = 0.1 # \ud559\uc2b5\ub960\n self.gamma = 0.99 # \ud560\uc778 \uacc4\uc218\n self.epsilon = 0.1 # \ud0d0\uc0c9 \ud655\ub960\n\n def choose_action(self, state):\n if np.random.rand() < self.epsilon: # \ud0d0\uc0c9\n return np.random.choice(range(len(self.env.action_space)))\n else: # \uac1c\ubc1c\n return np.argmax(self.q_table[state[0], state[1]])\n\n def update_q_value(self, state, action, reward, next_state):\n best_next_action = np.argmax(self.q_table[next_state[0], next_state[1]])\n td_target = reward + self.gamma * self.q_table[next_state[0], next_state[1], best_next_action]\n td_error = td_target - self.q_table[state[0], state[1], action]\n self.q_table[state[0], state[1], action] += self.alpha * td_error\n\n def train(self, episodes):\n for episode in range(episodes):\n state = self.env.reset()\n done = False\n while not done:\n action = self.choose_action(state)\n next_state, reward, done = self.env.step(self.env.action_space[action])\n self.update_q_value(state, action, reward, next_state)\n state = next_state\n<\/code><\/pre>\n3.3. \uacb0\uacfc \ud655\uc778<\/h3>\n
\ub9c8\uc9c0\ub9c9\uc73c\ub85c, \ud559\uc2b5\uc744 \uc218\ud589\ud558\uace0 \ucd5c\uc885 Q-\ud14c\uc774\ube14\uc744 \ucd9c\ub825\ud558\uc5ec \uc5d0\uc774\uc804\ud2b8\uac00 \uc5b4\ub5bb\uac8c \ud559\uc2b5\ud588\ub294\uc9c0\ub97c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
if __name__ == \"__main__\":\n env = GridWorld()\n agent = QLearningAgent(env)\n agent.train(1000)\n\n # Q-\ud14c\uc774\ube14 \ucd9c\ub825\n print(\"Final Q-Table:\")\n print(agent.q_table)\n<\/code><\/pre>\n\uacb0\ub860<\/h2>\n
\uc774\uc0c1\uc73c\ub85c \uac15\ud654\ud559\uc2b5\uc5d0\uc11c \ubcf4\uc0c1 \ud568\uc218\uc758 \uc911\uc694\uc131\uacfc \uc124\uacc4 \uc2dc \uace0\ub824 \uc0ac\ud56d, \uadf8\ub9ac\uace0 \uc2e4\uc81c \ubcf4\uc0c1 \uc124\uacc4\ub97c \uc704\ud55c \uc608\uc2dc\ub97c \uc0b4\ud3b4\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \ubcf4\uc0c1 \ud568\uc218\ub294 \uc5d0\uc774\uc804\ud2b8\uc758 \ud559\uc2b5 \ud6a8\uacfc\uc640 \ud589\ub3d9\uc744 \ubcf8\uc9c8\uc801\uc73c\ub85c \ud615\uc131\ud558\ub294 \uc694\uc18c\ub85c, \uc774\ub294 \uac15\ud654\ud559\uc2b5\uc758 \uc131\uacf5\uc5d0 \ub9e4\uc6b0 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4. \ud5a5\ud6c4 \ub2e4\uc591\ud55c \ud658\uacbd\uacfc \uc0ac\ub840\uc5d0 \ub300\ud574 \uc9c0\uc18d\uc801\uc73c\ub85c \uc5f0\uad6c\ud558\uc5ec, \ub354 \ud6a8\uc728\uc801\uc774\uace0 \ud6a8\uacfc\uc801\uc778 \ubcf4\uc0c1 \ud568\uc218\ub97c \uc124\uacc4\ud574 \ub098\uac00\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4.<\/p>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
\uac15\ud654\ud559\uc2b5(Deep Reinforcement Learning) \ubd84\uc57c\uc5d0\uc11c \ubcf4\uc0c1 \ud568\uc218(reward function)\ub294 \uc5d0\uc774\uc804\ud2b8\uc758 \ud559\uc2b5\uacfc \uc131\ub2a5\uc744 \uacb0\uc815\uc9d3\ub294 \ud575\uc2ec \uc694\uc18c\ub85c, \uc774\ub97c \uc801\uc808\ud788 \uc124\uacc4\ud558\ub294 \uac83\uc774 \uc131\uacf5\uc801\uc778 \ubaa8\ub378 \uad6c\ucd95\uc758 \ud544\uc218 \uc870\uac74\uc785\ub2c8\ub2e4. \ubcf4\uc0c1 \ud568\uc218\ub294 \uc5d0\uc774\uc804\ud2b8\uac00 \ud658\uacbd\uc5d0\uc11c \ud2b9\uc815 \ud589\ub3d9\uc744 \ucde8\ud588\uc744 \ub54c \ubc1b\ub294 \ud53c\ub4dc\ubc31\uc73c\ub85c, \uc5d0\uc774\uc804\ud2b8\uac00 \ubaa9\ud45c\ub97c \ud5a5\ud574 \ub098\uc544\uac00\uac70\ub098 \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \uc120\ud0dd\ud558\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \ubcf4\uc0c1 \ud568\uc218\uc758 \uc911\uc694\uc131\uacfc \uc774\ub97c \uc124\uacc4\ud560 \ub54c \uace0\ub824\ud574\uc57c \ud560 \uc0ac\ud56d, \uadf8\ub9ac\uace0 \uc2e4\uc81c \uc608\uc2dc\ub97c \ud1b5\ud574 … \ub354 \ubcf4\uae30 “12. \ubcf4\uc0c1 \ud568\uc218(Reward Function) \uc124\uacc4\uc758 \uc911\uc694\uc131, \ubcf4\uc0c1 \uc124\uacc4 \uc2dc \uace0\ub824\uc0ac\ud56d \ubc0f \uc608\uc2dc”<\/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-40490","post","type-post","status-publish","format-standard","hentry","category-213"],"yoast_head":"\n12. \ubcf4\uc0c1 \ud568\uc218(Reward Function) \uc124\uacc4\uc758 \uc911\uc694\uc131, \ubcf4\uc0c1 \uc124\uacc4 \uc2dc \uace0\ub824\uc0ac\ud56d \ubc0f \uc608\uc2dc - \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\" 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\ucde8\ud588\uc744 \ub54c \ubc1b\ub294 \ud53c\ub4dc\ubc31\uc73c\ub85c, \uc5d0\uc774\uc804\ud2b8\uac00 \ubaa9\ud45c\ub97c \ud5a5\ud574 \ub098\uc544\uac00\uac70\ub098 \ucd5c\uc801\uc758 \ud589\ub3d9\uc744 \uc120\ud0dd\ud558\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \ubcf4\uc0c1 \ud568\uc218\uc758 \uc911\uc694\uc131\uacfc \uc774\ub97c \uc124\uacc4\ud560 \ub54c \uace0\ub824\ud574\uc57c \ud560 \uc0ac\ud56d, \uadf8\ub9ac\uace0 \uc2e4\uc81c \uc608\uc2dc\ub97c \ud1b5\ud574 … \ub354 \ubcf4\uae30 "12. \ubcf4\uc0c1 \ud568\uc218(Reward Function) \uc124\uacc4\uc758 \uc911\uc694\uc131, \ubcf4\uc0c1 \uc124\uacc4 \uc2dc \uace0\ub824\uc0ac\ud56d \ubc0f \uc608\uc2dc"\" \/>\n<meta property=\"og:url\" content=\"https:\/\/atmokpo.com\/w\/40490\/\" \/>\n<meta property=\"og:site_name\" content=\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"article:published_time\" content=\"2024-11-04T01:52:09+00:00\" \/>\n<meta property=\"article:modified_time\" 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