๐Ÿ˜‰/ํ”„๋กœ์ ํŠธ ์ฐธ๊ณ  7

[๋ฒ”์ฃ„์˜ˆ์ธก] ๋„ค์ด๋ฒ„ ์ง€๋„ vs ์นด์นด์˜ค ๋งต

[sw๋ถ„์„] ์นด์นด์˜ค๋งต Vs ๋„ค์ด๋ฒ„์ง€๋„, ๋” ์ข‹์€ ์ง€๋„ ์•ฑ์€? ์•ž์„  2๊ฐœ์˜ ํฌ์ŠคํŒ…์—์„œ๋Š” ์นด์นด์˜ค๋งต์„ sw๋ถ„์„ ์ œํ’ˆ์œผ๋กœ ์„ ํƒํ•œ ์ด์œ ์™€ ์นด์นด์˜ค๋งต์˜ ํŠน์ง•์— ๋Œ€ํ•ด ์•Œ์•„๋ณด์•˜์Šต๋‹ˆ๋‹ค. ์ด๋ฒˆ์—๋Š” ๊ฐ™์€ ์ง€๋„ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์ธ ๋„ค์ด๋ฒ„์ง€๋„์™€ ์–ด๋Š ์ œํ’ˆ์ด ๋” ํŽธ๋ฆฌํ•œ์ง€ ์žฅ/ velog.io ๋‹จ, ๋„ค์ด๋ฒ„ ์ง€๋„ API, ์นด์นด์˜ค ๋งต API ์ค‘ ๋„ค์ด๋ฒ„ ์ง€๋„ API๋ฅผ ํ™œ์šฉํ•œ ์„ค๋ช… ์ž๋ฃŒ๋“ค์ด ๋Œ€์ฒด์ ์œผ๋กœ ๋” ๋งŽ์€ ๋“ฏ ํ•˜๋‹ค.

[๋ฒ”์ฃ„์˜ˆ์ธก] ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ ์ถœ์ฒ˜

๋‚ ์”จ(๋‹จ์œ„ : ์‹œ) ใ…ก ๋งํฌ ์›”๋ณ„ ๋ฒ”์ฃ„ ๋ฐ์ดํ„ฐ(๋‹จ์œ„ : ๊ตฌ) ใ…ก ๋งํฌ ์‹œ๊ฐ„๋Œ€๋ณ„ ๋ฒ”์ฃ„ ๋ฐ์ดํ„ฐ(๋‹จ์œ„ : ๊ตฌ) ใ…ก ๋งํฌ CCTV ์œ„์น˜(๋‹จ์œ„ : ์ขŒํ‘œ) ใ…ก ๋งํฌ ๊ฒฝ์ฐฐ์„œ ์œ„์น˜(๋‹จ์œ„ : ์ขŒํ‘œ) ใ…ก ๋งํฌ ์œ ๋™์ธ๊ตฌ(๋‹จ์œ„ : ๊ตฌ) ใ…ก ๋งํฌ ๋“ฑ๋ก์ธ๊ตฌ(๋‹จ์œ„ : ๊ตฌ) ใ…ก ๋งํฌ ์ธ๊ตฌ๋ฐ€๋„(๋‹จ์œ„ : ๋™) ใ…ก ๋งํฌ

[๋ฒ”์ฃ„์˜ˆ์ธก] ๋„๋กœ๋ช… ์ฃผ์†Œ ์œ„๋„/๊ฒฝ๋„ ์ž๋™๋ณ€ํ™˜

์ถœ์ฒ˜ : ์ฒœ์žฌ ์œ ํŠœ๋ธŒ 1. ๊ตฌ๊ธ€ ์Šคํ”„๋ ˆ๋“œ ์‹œํŠธ์— ๋ฐ์ดํ„ฐ๋ฅผ ์˜ฌ๋ฆฐ๋‹ค. 2. ๋ถ€๊ฐ€๊ธฐ๋Šฅ์— 'Geocode'๋ฅผ ์„ค์น˜ํ•œ๋‹ค. 3. ์ฃผ์†Œ๊ฐ€ ์žˆ๋Š” ์ปฌ๋Ÿผ์„ ์ž…๋ ฅํ•˜๊ณ  ์‹คํ–‰ํ•œ๋‹ค. 4. ์ฃผ์†Œ ์˜ค๋ฅธ์ชฝ์— ์œ„๋„/๊ฒฝ๋„ ์—ด์ด ์ƒ์„ฑ๋˜๋ฉฐ ๊ธฐ๋ก๋œ๋‹ค.

[๋ฒ”์ฃ„์˜ˆ์ธก] ๋…ผ๋ฌธ : ๋จธ์‹ ๋Ÿฌ๋‹ ๊ธฐ๋ฐ˜ ๋ฒ”์ฃ„๋ฐœ์ƒ ์œ„ํ—˜์ง€์—ญ ์˜ˆ์ธก

๋จธ์‹ ๋Ÿฌ๋‹๊ธฐ๋ฐ˜ ๋ฒ”์ฃ„๋ฐœ์ƒ ์œ„ํ—˜์ง€์—ญ ์˜ˆ์ธก Predicting Crime Risky Area Using Machine Learning ํ•œ๊ตญ์ง€๋ฆฌ์ •๋ณดํ•™ํšŒ์ง€ v.21 no.4 , 2018๋…„, pp.64 - 80 ํ—ˆ์„ ์˜, ๊น€์ฃผ์˜, ๋ฌธํƒœํ—Œ ์›๋ฌธ๋ณด๊ธฐ - ScienceON ์ด ์›๋ฌธ์€ ScienceON์—์„œ ์ œ๊ณตํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. scienceon.kisti.re.kr ์š”์•ฝ 1. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• ์ง€๋„ํ•™์Šต ๋ชจ๋ธ ์ค‘ ์˜์‚ฌ๊ฒฐ์ •๋‚˜๋ฌด, ๋žœ๋คํฌ๋ ˆ์ŠคํŠธ, SVM์„ MATLAB ํŒจํ‚ค์ง€๋กœ ๋น„๊ต ๋ถ„์„. ๋ฒ”์ฃ„ ๋ฐ์ดํ„ฐ๋ฅผ 8 : 2 ๋กœ ๋‚˜๋ˆ  ๊ฐ๊ฐ ํ•™์Šต, ํ”ผ๋“œ๋ฐฑ์— ์‚ฌ์šฉ. 2. ๋ฐ์ดํ„ฐ ๊ตฌ์ถ• ๋ฒ”์ฃ„์ •๋ณด(์‚ฌ๋ก€์ง€์—ญ์˜ 2008๋…„, 2011๋…„ 4906๊ฑด์˜ 5๋Œ€๋ฒ”์ฃ„ ๋ฐœ์ƒ ์ •๋ณด) ๋ฒ”์ฃ„ : ๊ณ„์ ˆ, ์‹œ๊ฐ„๋Œ€, ๋ฒ”์ฃ„์œ ํ˜• ๋‚ ์”จ์ •๋ณด(์‹œ๊ฐ„์ ์œผ๋กœ ๋ณ€ํ™”, ๋ฒ”์ฃ„์™€ ์—ฐ๊ด€์„ฑ์ด ๋†’๋‹ค๋Š” ์—ฐ๊ตฌ ๆœ‰) ๋‚ ์”จ ..

[ADD] ๋…ผ๋ฌธ : Case-Based Learning in Goal-Driven Autonomy Agents for Real-Time Strategy Combat Tasks

Case-Based Learning in Goal-Driven Autonomy Agents for Real-Time Strategy Combat Tasks ์‹ค์‹œ๊ฐ„ ์ „๋žต ์ „ํˆฌ ์ž‘์—…์„ ์œ„ํ•œ ๋ชฉํ‘œ ์ค‘์‹ฌ ์ž์œจ ์—์ด์ „ํŠธ์˜ ์‚ฌ๋ก€ ๊ธฐ๋ฐ˜ ํ•™์Šต Ulit Jaidee1, Hรฉctor Muรฑoz-Avila1, and David W. Aha2 1Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA Keywords: Case-based learning, goal-driven autonomy, real-time strategy ์š”์•ฝ. ์‹ค์‹œ๊ฐ„ ์ „๋žต ๊ฒŒ์ž„์„ ์œ„ํ•œ ๋ชฉํ‘œ ์ค‘์‹ฌ ์ž์œจ ์—์ด์ „ํŠธ(GDA)์—์„œ ์‚ฌ๋ก€ ๊ธฐ๋ฐ˜ ํ•™์Šต ๊ธฐ์ˆ ์„ ์‚ฌ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ..

[ADD] ModifiedTensorboard object has no attribute '_write_logs' ์—๋Ÿฌ

https://pythonprogramming.net/training-deep-q-learning-dqn-reinforcement-learning-python-tutorial/ # ModifiedTensorboard ํด๋ž˜์Šค์— ๋‹ค์Œ ๋ฉ”์†Œ๋“œ ์ถ”๊ฐ€ def _write_logs(self, logs, index): for name, value in logs.items(): if name in ['batch', 'size']: continue summary = tf.Summary() summary_value = summary.value.add() summary_value.simple_value = value summary_value.tag = name self.writer.add_summary(summary, in..