๋ณธ๋ฌธ ๋ฐ”๋กœ๊ฐ€๊ธฐ

์ „์ฒด ๊ธ€

(116)
[๋…ผ๋ฆฌ์„ค๊ณ„] Verilog-HDL ์„ค๊ณ„ 1. ๊ธฐ๋ณธ 1) Module - top module - ํ•˜์œ„ module - test module modul module_name(port_list); port ์„ ์–ธ reg ์„ ์–ธ wire ์„ ์–ธ parameter ์„ ์–ธ gate modeling data flow modeling behavioral modeling structural modeling ํ•˜์œ„๋ชจ๋“ˆ ํ˜ธ์ถœ endmodule - Verilog HDL๋กœ ํ‘œํ˜„๋˜๋Š” ๋…ผ๋ฆฌํšŒ๋กœ๋Š” "module~endmodule" ์•ˆ์— ์žˆ์–ด์•ผ ํ•จ - ๋ชจ๋“  ๋ฌธ์žฅ์€ ; ๋กœ ๋๋‚˜๊ณ , "end~"๋กœ ์‹œ์ž‘ํ•˜๋Š” ์˜ˆ์•ฝ์–ด์—๋Š” ; ์—†์Œ - ์ด๋ฆ„ ๋˜๋Š” ์‹๋ณ„์ž๋Š” ์†Œ๋ฌธ์ž์™€ ๋Œ€๋ฌธ์ž๋ฅผ ๊ตฌ๋ณ„ - ์˜ˆ์•ฝ์–ด๋Š” ๋ฐ˜๋“œ์‹œ ์†Œ๋ฌธ์ž์ž„ - module ์ด๋ฆ„์€ ์˜๋ฌธ์ž์™€ ์–ธ๋”๋ฐ”๋กœ ์‹œ์ž‘ ๊ฐ€๋Šฅ - ์ฃผ์„์€ // ๋˜๋Š” /* */ 2..
[๋…ผ๋ฆฌ์„ค๊ณ„] 2. ๋ถ€์šธ๋Œ€์ˆ˜์™€ ๋…ผ๋ฆฌ๊ฒŒ์ดํŠธ 1. ๋ถ€์šธ ์Šค์œ„์นญ ๋Œ€์ˆ˜ - ๋ถ€์šธ ๋Œ€์ˆ˜ : ๋…ผ๋ฆฌ ์—ฐ์‚ฐ์ž and, or, not์„ ์‚ฌ์šฉํ•˜์—ฌ ๋…ผ๋ฆฌ์  ๊ธฐ๋Šฅ์„ ์ฒ˜๋ฆฌํ•˜๋Š” ๋…ผ๋ฆฌ ์ˆ˜ํ•™ - ๋ถ€์šธ์‹ : ๋…ผ๋ฆฌ์  ๊ธฐ๋Šฅ์„ ๊ธฐํ˜ธ๋กœ ๋‚˜ํƒ€๋‚ธ ์‹ - ๋…ผ๋ฆฌ๋ณ€์ˆ˜ : ์‹œ๊ฐ„์— ๋”ฐ๋ผ ๋ณ€ํ•˜๋Š” ๋…ผ๋ฆฌ์น˜๋ฅผ ๊ฐ–๋Š” ์–‘ - ๋…ผ๋ฆฌ์—ฐ์‚ฐ์ž : ๋…ผ๋ฆฌ ์‹œ์Šคํ…œ์„ ํ•ด์„ํ•˜๊ณ  ์„ค๊ณ„ํ•˜๋Š”๋ฐ ์‚ฌ์šฉ๋˜๋Š” ๊ธฐ๋ณธ์ ์ธ ๊ธฐ๋Šฅ - ๋…ผ๋ฆฌํ•จ์ˆ˜ : ์ž„์˜์˜ ์‹œ์Šคํ…œ์ด ๊ฐ–๊ณ ์žˆ๋Š” ๋…ผ๋ฆฌ์ ์ธ ๊ธฐ๋Šฅ - ์ง„๋ฆฌํ‘œ : ๋ชจ๋“  ๊ฐ€๋Šฅํ•œ ๊ฒฝ์šฐ์˜ ๋…ผ๋ฆฌ์ ์ธ ์ž…๋ ฅ๊ณผ ์ถœ๋ ฅ๊ณผ์˜ ๊ด€๊ณ„๋ฅผ ๋‚˜ํƒ€๋‚ธ ํ‘œ 2. ๋ถ€์šธ ํ•จ์ˆ˜ - Closure : + /· (and / or) - ๋‹จ์œ„์› (identity element) : ์›๋ž˜ ๊ผด์ด ๋‚˜์˜ค๊ฒŒ ๋งŒ๋“œ๋Š” ๊ฐ’ (or์ผ ๋•Œ๋Š” 0, and ์ผ ๋•Œ๋Š” 1) ex) x+0 = 0+x = x x · 1 = 1 · x = x - ๊ตํ™˜๋ฒ•์น™, ๋ถ„๋ฐฐ๋ฒ•์น™ - ๋ณด์ˆ˜ e..
[๋…ผ๋ฆฌ์„ค๊ณ„] 1. ๋””์ง€ํ„ธ ์‹œ์Šคํ…œ๊ณผ 2์ง„์ˆ˜์ฒด๊ณ„ 1. Digital System 1) Analog & Digital -Analog ์‹ ํ˜ธ : ์—ฐ์†์ ์œผ๋กœ ํ‘œํ˜„๋œ ์‹ ํ˜ธ -Digital ์‹ ํ˜ธ : ์ด์‚ฐ์ ์œผ๋กœ ํ‘œํ˜„๋œ ์‹ ํ˜ธ -๋ถ€ํ˜ธํ™” : ์‹ ํ˜ธ์˜ ํ‘œํ˜„ ๋ฐฉ์‹์„ ๋ฐ”๊พธ์–ด ๋‚˜ํƒ€๋‚ด๋Š” ๊ฒƒ 2) Analog-Digital ๋ณ€ํ™˜ -Sampling (์ƒ˜ํ”Œ๋ง) : ์ผ์ •ํ•œ ์‹œ๊ฐ„ ๊ฐ„๊ฒฉ์œผ๋กœ ๋ถ„ํ•ดํ•˜์—ฌ ๋‚˜ํƒ€๋‚ด๋Š” ๊ฒƒ. Sampling ์ˆซ์ž๊ฐ€ ๋งŽ์„ ์ˆ˜๋ก ๊ฐ„๊ฒฉ์ด ์ข์•„์ ธ ์ •ํ™•๋„ ์ƒ์Šน. ์ ์„์ˆ˜๋ก ๊ฐ„๊ฒฉ์ด ๋„“์–ด์ ธ ์ •ํ™•๋„ ํ•˜๋ฝ. ex) 1์ดˆ์ผ ๋•Œ ๊ฐ’, 2์ดˆ์ผ ๋•Œ ๊ฐ’, .... -Quantization (์–‘์žํ™”) : ์‹ ํ˜ธ์น˜๋ฅผ ์ด์‚ฐ์ ์œผ๋กœ ํ‘œํ˜„ํ•˜๋Š” ๊ฒƒ, ๋ฐ์ดํ„ฐ๋ฅผ ์ด์‚ฐ์ ์œผ๋กœ ํ‘œํ˜„ํ•œ๋‹ค. 3) ์–‘์žํ™” - Analog ๊ฐ’ : 0.00, 2.53, 9.4 ... - Digital ๊ฐ’ : 0000 , 0001, 0010, ..
[์ธ๊ณต์ง€๋Šฅ] 10. Planning 1. Planning Problem Representation 1) Planning Domain Definition Language (PDDL) : search problem์„ ์ •์˜ํ•˜๋Š”๋ฐ ํ•„์š”ํ•œ 4๊ฐ€์ง€ ์š”์†Œ๋ฅผ ์„ค๋ช…ํ•œ๋‹ค. -> initial state, actions, result, goal test โ‘  States : ๊ฐ๊ฐ์˜ state๋Š” "groundํ•˜๊ณ  functionlessํ•˜๊ณ  atomsํ•œ" conjunction of fluents๋กœ ํ‘œํ˜„๋œ๋‹ค. ์ฆ‰ variable์ด ์—†์–ด์•ผ ํ•ด์š” Database semantic์ด ์‚ฌ์šฉ๋˜๋Š”๋ฐ - closed-world assumption : ์–ด๋–ค fluents๋„ false๋กœ ์–ธ๊ธ‰๋˜์ง€ ์•Š๊ณ  - unique names assumption : ์„œ๋กœ ๋‹ค๋ฅธ constants๋Š” ๊ตฌ..
[์ธ๊ณต์ง€๋Šฅ] 8~9. First-Order Logic(FOL) 1. Syntax and Semantics : propositional logic, ๋ช…์ œ๋…ผ๋ฆฌํ•™์€ ์ด ์„ธ์ƒ์˜ ๋ชจ๋“  ๋ฌธ์ œ๋ฅผ propositional symbol๋กœ ๋‚˜ํƒ€๋‚ด๊ณ  ์˜ค์ง true/false์˜ ๊ฐ’๋งŒ ๊ฐ€์ง„๋‹ค. ๋”ฐ๋ผ์„œ ์ด ์„ธ์ƒ์— ๋งŽ์€ object๋“ค์„ ํ‘œํ˜„ํ•˜๊ธฐ์—” ๋ถ€์กฑํ•œ ๋ฉด์ด ์žˆ๋‹ค. (lack the expressive power) ์šฐ๋ฆฌ๊ฐ€ ์ž์—ฐ์–ด์˜ ๋ฌธ๋ฒ•์„ ์‚ดํŽด๋ณด๋ฉด, ๋Œ€๋ถ€๋ถ„์˜ elements๋“ค์ด ๋ช…์‚ฌ์™€ ๋ช…์‚ฌ๊ตฌ๋กœ object๋ฅผ ๋‚˜ํƒ€๋‚ด๊ณ , ๋™์‚ฌ๋‚˜ ๋™์‚ฌ๊ตฌ๋กœ object๊ฐ„์˜ relation์„ ๋‚˜ํƒ€๋‚ธ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด relation์ค‘์˜ ์ผ๋ถ€๋Š” ์–ด๋–ค input์ด ์ฃผ์–ด์กŒ์„ ๋•Œ ํ•˜๋‚˜์˜ value๋ฅผ ๋‚ด๋ฑ‰๋Š” function(object์˜ 1:1 ๊ด€๊ณ„)์ด๊ธฐ๋„ ํ•˜๋‹ค. First-order logic์€ ์ด ์„ธ์ƒ์—” object์™€ ์ด๋“ค์„ ..
[์ธ๊ณต์ง€๋Šฅ] 7. Propositional Logic - 3 5) Analysis of Resolution Algorithm resolution rule์€ ์–ด๋–ค completeํ•œ search algorithm๊ณผ ๊ฒฐํ•ฉํ•  ๋•Œ completeํ•œ inference algorithm์„ ๋งŒ๋“ค์–ด๋‚ธ๋‹ค. PL-Resolution์ด completeํ•จ์„ ๋ณด์ด๊ธฐ ์œ„ํ•ด์„œ resolution closure = RC(S)๋ฅผ ์ •์˜ํ•œ๋‹ค. RC(S)๋ž€ "clause์˜ ์ง‘ํ•ฉ S์— ๋“ค์–ด์žˆ๋Š” clause์™€ ๊ทธ clause๋ผ๋ฆฌ resolution์„ ํ†ตํ•ด ๋งŒ๋“ค์–ด์ง„ ๋ชจ๋“  clause๋“ค"์— ๋˜ resolution์„ ๋ฐ˜๋ณตํ•ด์„œ ์ ์šฉํ•ด์„œ ๋งŒ๋“ค ์ˆ˜ ์žˆ๋Š” ๋ชจ๋“  clause๋“ค์˜ ์ง‘ํ•ฉ์„ ๋งํ•œ๋‹ค. RC(S)๊ฐ€ ์œ ํ•œํ•˜๋‹ค๋Š” ๊ฒƒ์€ ๋ช…๋ฐฑํžˆ ์•Œ ์ˆ˜ ์žˆ๋‹ค. ์œ ํ•œํ•œ symbol๋“ค๋กœ ๋งŒ๋“ค ์ˆ˜ ์žˆ๋Š” clause๋Š” ์œ ํ•œ๊ฐœ ์กด์žฌํ•  ๊ฒƒ์ด๊ณ , ..
[์ธ๊ณต์ง€๋Šฅ] 7. Propositional logic - 2 3. Theorem Proving : Theorem Proving์ด๋ž€ ์šฐ๋ฆฌ๊ฐ€ ์ด๋ฏธ ์•Œ๊ณ ์žˆ๋Š” ์‚ฌ์‹ค(Knowledge base)์˜ sentence๋“ค์— ์ถ”๋ก  ๊ทœ์น™(Inference rule)์„ ์ ์šฉํ•ด์„œ ์ƒˆ๋กœ์šด ์‚ฌ์‹ค์„ ์•Œ์•„๋‚ด๋Š” ๊ฒƒ/ ์ƒˆ๋กœ์šด ๋ฌธ์žฅ์„ ๋งŒ๋“ค์–ด๋‚ด๋Š” ๊ฒƒ์„ ๋งํ•œ๋‹ค. ๋งŒ์•ฝ model์˜ ๊ฐœ์ˆ˜๊ฐ€ ๋งŽ๊ณ , proof์˜ ๊ธธ์ด๊ฐ€ ์งง๋‹ค๋ฉด, theorem proving์ด model checking๋ณด๋‹ค ๋” ํšจ์œจ์ ์ด๋‹ค. 1) Inference Rules - Modus Ponens : α⇒β์ด๊ณ  α๊ฐ€ true๋ฉด β๋„ true๋‹ค. - And-Elimination : α and β๊ฐ€ true์ด๋ฉด α๋Š” ํ•ญ์ƒ true์ด๋‹ค - Logical equivalences : α and β๊ฐ€ true์ด๋ฉด β and α๋„ true์ด๋‹ค. - α ์™€..
[์ธ๊ณต์ง€๋Šฅ] 7. Propositional logic - 1 1. Propositional Logic (๋ช…์ œ ๋…ผ๋ฆฌํ•™) 1) Example ์ด๋ฒˆ ๋‹จ์› ๋‚ด๋‚ด ์ง€๊ฒน๋„๋ก ๋ณด๊ฒŒ ๋  Wumpus World game์ด๋‹ค. ์ด ๊ฒŒ์ž„์€ (1,1)์—์„œ ์šฉ์‚ฌ๊ฐ€ ์ถœ๋ฐœํ•ด ๊ดด๋ฌผ๊ณผ ํ•จ์ •์„ ํ”ผํ•ด gold๋ฅผ ๋ฌด์‚ฌํžˆ ์ฐพ๋Š” ๊ฒƒ์ด ๋ชฉํ‘œ์ด๋‹ค. ํ•จ์ •์ด ์žˆ์œผ๋ฉด ํ•จ์ •์˜ ์‚ฌ๋ฐฉ์œผ๋กœ breeze ๋ฐ”๋žŒ์ด ๋ถˆ๊ณ , ๊ดด๋ฌผ์ด ์žˆ์œผ๋ฉด ๊ดด๋ฌผ์˜ ์‚ฌ๋ฐฉ์œผ๋กœ ์•…์ทจ strench๊ฐ€ ํ’๊ธด๋‹ค. ์ด ํžŒํŠธ๋ฅผ ์ด์šฉํ•ด ์ตœ์†Œํ•œ์œผ๋กœ ์›€์ง์—ฌ ๋ฌด์‚ฌํžˆ gold๋ฅผ ์ฐพ์œผ๋ฉด ๋œ๋‹ค. ์šฉ์‚ฌ๊ฐ€ ์–ด๋–ค Action์„ ์ทจํ•  ๋•Œ๋งˆ๋‹ค cost๊ฐ€ ๋“ ๋‹ค. ์ด๊ฑด ์•Œ์•„๋„ ๋˜๊ณ  ๋ชฐ๋ผ๋„ ๋˜๋Š”๋ฐ ์šฉ์‚ฌ๋Š” ํ™”์‚ด์„ ์  ์ˆ˜ ์žˆ๋‹ค. ํ™”์‚ด์„ ์˜๋ฉด ์ง์„  ๋ฐฉํ–ฅ์œผ๋กœ ์ญ‰ ๋‚ ์•„๊ฐ€๋Š”๋ฐ, ๊ดด๋ฌผ์ด ๋งž์œผ๋ฉด ์†Œ๋ฆฌ๋ฅผ ์ง€๋ฅด๋ฉด์„œ ์ฃฝ๋Š”๋‹ค. ์ด ์†Œ๋ฆฌ๋ฅผ ๋“ฃ๊ณ  ๊ดด๋ฌผ์˜ ์œ„์น˜๋ฅผ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋‹ค. ์šฉ์‚ฌ๋Š” ์ž๊ธฐ๊ฐ€ ์žˆ๋Š” ์นธ์—์„œ ์ •๋ณด..
[์ธ๊ณต์ง€๋Šฅ] 6. Constraint Satisfaction Problems 1. Problem Formulation as a CSP : ๋ฌธ์ œ ์ƒํ™ฉ์„ ํ‘œํ˜„ํ•˜๋Š” ๋ฐฉ๋ฒ• ์ค‘์—์„œ๋Š” factored represetation์ด ์žˆ๋‹ค. ์–ด๋–ค ๋ฌธ์ œ๊ฐ€ ์–ด๋–ค ์ œํ•œ์‚ฌํ•ญ, ์กฐ๊ฑด๋“ค(Constraint)๋ฅผ ๋งŒ์กฑ์‹œ์ผœ์•ผ ํ’€๋ฆฐ๋‹ค๊ณ  ํ•ด๋ณด์ž. Factored representation์€ ๊ฐ states๋ฅผ variable์„ ํ™œ์šฉํ•ด ํ‘œํ˜„ํ•˜๋Š” ๊ฒƒ์ด๊ณ (goal state ๋˜ํ•œ ๊ทธ๋ ‡๋‹ค), ์ด variable์— ํ• ๋‹น๋œ value๊ฐ’์ด constraint์„ ๋งŒ์กฑํ•˜๋Š” ๊ฐ’์ผ ๋•Œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ–ˆ๋‹ค๊ณ  ๋งํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ์ฆ‰, ์–ด๋–ค ๊ฐ’์„ ํ• ๋‹นํ•  ์ˆ˜ ์žˆ๋Š” variable๊ณผ ๋…ผ๋ฆฌ์—ฐ์‚ฐ์ž๋ฅผ ์ด์šฉํ•ด ์–ด๋–ค ๋ฌธ์ œ ์ƒํ™ฉ์„ ํ‘œํ˜„ํ•œ๋‹ค๊ณ  ํ•  ๋•Œ, ์ด๋Ÿฐ ๋ฌธ์ œ๋“ค์„ Constraint Satisfaction Problem์ด๋ผ๊ณ  ํ•œ๋‹ค. ( ์ง€๊ธˆ๊นŒ์ง€๋Š” autonomic..
[์ธ๊ณต์ง€๋Šฅ] 5. Adversarial Search(์ ๋Œ€์  ํƒ์ƒ‰) ์ด ๋‹จ์›์—์„œ๋Š” competitive multiagent environment, ์ฆ‰ ์„œ๋กœ ๊ฒฝ์Ÿ์ ์ธ ๋‘ agent๊ฐ€ ์žˆ๋Š” ์ƒํ™ฉ์„ ๋‹ค๋ฃฌ๋‹ค. ์ด๋Š” game์œผ๋กœ ์ž˜ ์•Œ๋ ค์ ธ ์žˆ๋Š” adversarial search problem์„ ๋งํ•œ๋‹ค. 1. Game 1) game์€ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์š”์†Œ๋“ค๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ๋‹ค. - S0 : The initial state. ๊ฒŒ์ž„์ด ์–ด๋–ค ์ƒํ™ฉ์—์„œ ์‹œ์ž‘๋˜๋Š”์ง€ - Player(s) : ๊ฐ state์—์„œ ์–ด๋Š player๊ฐ€ ์›€์ง์ผ ์ฐจ๋ก€์ธ์ง€ ์•Œ๋ ค์คŒ - Actions(s) : ๊ฐ state์—์„œ ์ทจํ•  ์ˆ˜ ์žˆ๋Š” move๋“ค์˜ ์ง‘ํ•ฉ์„ return - Result(s, a) : ์–ด๋–ค state s์—์„œ action a๋ฅผ ํ–ˆ์„ ๋•Œ result. transition model. - TerminalTest(s) :..