๋ณธ๋ฌธ ๋ฐ”๋กœ๊ฐ€๊ธฐ

๊ฐ•ํ™”ํ•™์Šต2

ํ•œ๋ˆˆ์— ๋ณด๋Š” ๋จธ์‹ ๋Ÿฌ๋‹ ํ•™์Šต ๋ฐฉ์‹ ๋น„๊ตํ‘œ (์ง€๋„ํ•™์Šต, ๋น„์ง€๋„ํ•™์Šต, ๊ฐ•ํ™”ํ•™์Šต) ๐Ÿ“š ๋ชฉ์ฐจ1. ๋จธ์‹ ๋Ÿฌ๋‹์˜ ์„ธ ๊ฐ€์ง€ ํ•™์Šต ๋ฐฉ์‹1-1. ์™œ ํ•™์Šต ๋ฐฉ์‹ ๊ตฌ๋ถ„์ด ์ค‘์š”ํ• ๊นŒ?1-2. ์„ธ ๊ฐ€์ง€ ํ•™์Šต ๋ฐฉ์‹ ์š”์•ฝ2. ์ง€๋„ํ•™์Šต (Supervised Learning)2-1. ์›๋ฆฌ์™€ ํŠน์ง•2-2. ์‚ฌ์šฉ ์‚ฌ๋ก€3. ๋น„์ง€๋„ํ•™์Šต (Unsupervised Learning)3-1. ์›๋ฆฌ์™€ ํŠน์ง•3-2. ์‚ฌ์šฉ ์‚ฌ๋ก€4. ๊ฐ•ํ™”ํ•™์Šต (Reinforcement Learning)4-1. ์›๋ฆฌ์™€ ํŠน์ง•4-2. ์‚ฌ์šฉ ์‚ฌ๋ก€5. ์„ธ ํ•™์Šต ๋ฐฉ์‹ ์š”์•ฝ ๋ฐ ์„ ํƒ ํŒ 1. ๋จธ์‹ ๋Ÿฌ๋‹์˜ ์„ธ ๊ฐ€์ง€ ํ•™์Šต ๋ฐฉ์‹1-1. ์™œ ํ•™์Šต ๋ฐฉ์‹ ๊ตฌ๋ถ„์ด ์ค‘์š”ํ• ๊นŒ?๋จธ์‹ ๋Ÿฌ๋‹์—์„œ ๋ฐ์ดํ„ฐ๋ฅผ ์–ด๋–ป๊ฒŒ ํ•™์Šตํ•˜๋Š๋ƒ์— ๋”ฐ๋ผ **์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์ข…๋ฅ˜์™€ ์ ์šฉ ๋ฐฉ์‹์ด ์™„์ „ํžˆ ๋‹ฌ๋ผ์ง‘๋‹ˆ๋‹ค.** ๋Œ€ํ‘œ์ ์ธ ๋ฐฉ์‹์€ ์ง€๋„ํ•™์Šต(Supervised Learning), ๋น„์ง€๋„ํ•™์Šต(Unsupervised Lea.. 2025. 4. 4.
AI ์ดˆ๋ณด์ž๋ฅผ ์œ„ํ•œ ๊ฐ•ํ™”ํ•™์Šต(Reinforcement Learning) ์™„์ „ ์ •๋ณต ๐Ÿ“š ๋ชฉ์ฐจ 1. ๊ฐ•ํ™”ํ•™์Šต์ด๋ž€ ๋ฌด์—‡์ธ๊ฐ€? 1-1. ๊ฐ•ํ™”ํ•™์Šต์˜ ์ •์˜ 1-2. ๋‹ค๋ฅธ ํ•™์Šต ๋ฐฉ์‹๊ณผ์˜ ์ฐจ์ด์  2. ๊ฐ•ํ™”ํ•™์Šต์˜ ํ•ต์‹ฌ ๊ฐœ๋… 2-1. ์—์ด์ „ํŠธ์™€ ํ™˜๊ฒฝ 2-2. ๋ณด์ƒ ํ•จ์ˆ˜์™€ ์ •์ฑ… 2-3. ํƒํ—˜๊ณผ ํ™œ์šฉ (Exploration vs Exploitation) 3. ๊ฐ•ํ™”ํ•™์Šต ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ข…๋ฅ˜ 3-1. Q-Learning 3-2. SARSA 3-3. DQN (Deep Q-Network) 3-4. ์ •์ฑ… ๊ธฐ๋ฐ˜: REINFORCE, Actor-Critic 4. ๊ฐ•ํ™”ํ•™์Šต์˜ ํ™œ์šฉ ์‚ฌ๋ก€ .. 2025. 3. 21.