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도서 소개

인공지능(제4판): 현대적 접근방식 1권

전 세계 1,500개 이상의 대학에서 교재로 사용하는 인공지능 교과서!

 

도서구매 사이트(가나다순)

 [교보문고]  [도서11번가]  [알라딘]  [예스이십사]  [인터파크]  [쿠팡]

출판사 제이펍
저작권사 Pearson
원서명 Artificial Intelligence: A Modern Approach 4/E(ISBN: 9780134610993)
지은이 스튜어트 러셀, 피터 노빅
옮긴이 류광
출판일 2021년 8월 25일
페이지 932쪽
판   형 46배판변형(188 x 245 x 38.5)
제   본 무선(soft cover)
정   가 42,000원
ISBN 979-11-91600-31-5 (93000)
키워드 인공지능, AI, 로봇공학, 기계학습, 머신러닝, 자연어처리, 딥러닝, 심층학습, 확률적 추론, 지능적 에이전트, 컴퓨터 비전
분   야 컴퓨터 공학 / 인공지능

 

관련 사이트

 아마존 도서소개 페이지

 저작권사 도서소개 페이지

독자 Q&A(역자 홈페이지)

 

관련 포스트

 2021/8/12 - 인공신경망의 부활과 심층학습의 눈부신 성과를 반영한 인공지능 연구의 결정판!

 

관련 시리즈

아이러브 A.I.(IA.I.)

 

관련 도서

패턴 인식과 머신 러닝

단단한 강화학습: 강화학습 기본 개념을 제대로 정리한 인공지능 교과서

 

관련 파일 다운로드

 예제 코드 다운로드

 컬러 그림 다운로드

■ 참고문헌:

인공지능(제4판) 전체 참고문헌.pdf
1.21MB

■ 1, 2권 전체 찾아보기:

인공지능(제4판) 전체 찾아보기.pdf
1.88MB

 

교재 검토용 증정 안내

■ 학교 및 학원에서 교재 선정을 위해 책을 파일로 검토해보고자 하시는 분들은 다음의 페이지에서 신청 양식을 작성해주시기 바랍니다. 확인 후 연락을 드리도록 하겠습니다. http://goo.gl/vBtPo3

 

강의보조 자료

■ 교재로 채택하신 분들은 메일(textbook@jpub.kr)을 보내주시면 본문의 그림과 표 자료를 보내드리겠습니다.

■ 전판인 3판까지는 책의 본문에 실렸던 연습문제가 4판에서는 원서부터가 웹 제공으로 바뀌었으나, 21년 8월 현재까지 완성되지 않은 상태여서 책에 번역하여 싣지 못한 연습문제 영문 링크를 다음과 같이 알려드립니다:
https://aimacode.github.io/aima-exercises/ 

 

샘플 PDF(표지, 차례, 옮긴이 머리말, 머리말, 각 권의 베타리더 후기, 1장 '소개', 19장 '견본에서 배우는 학습' 일부)

인공지능(제4판)_Sample.pdf
2.32MB

정오표 페이지

■ (등록되는 대로 링크를 걸어드리겠습니다)

 

도서구매 사이트(가나다순)

 [교보문고]  [도서11번가]  [알라딘]  [예스이십사]  [인터파크]  [쿠팡]  

 

도서 소개

전 세계 1,500개 이상의 대학에서 교재로 사용하는 인공지능 교과서!

 

‘인공지능 바이블’로 통하는 이 책은 이미 3판에서도 인공지능 연구의 결정판으로서의 위치를 확고히 한 바 있다. 최소 134개국 1,536개 이상의 대학에서 교재로 사용하고 있으며(미국에서만 557개 대학에서 채택), 전 세계의 교육자들은 이 책을 다음과 같이 칭송하고 있다.

 

인공지능에 관한 책을 딱 하나만 가진다면, 그 책은 반드시 이 책이어야 한다. 이 책은 해박하고 상세하며, 흥미롭고 유용한 통찰로 가득하다. 

— 하버드대학교의 아비 페퍼 교수

 

이번에도 저자들은 훌륭한 교과서를 좀 더 훌륭한 교과서로 만드는 데 성공했다. 직관적이고 명확한 서술을 통해 복잡한 문제를 쉽게 만드는 영리한 글쓰기를 보여주었으며, 그것을 이토록 광범위한 주제에 적용했다는 점에 무한한 존경을 표한다. 나는 최근 인공지능에 관한 관심이 부활한 데에는 이런 뛰어난 교과서 덕분이라고 확신한다.

— 독일 다름슈타트 공과대학의 볼프강 비벨 교수

 

이 책은 인공지능의 최전선에 대한 확신과 낙관주의, 그리고 전염력 있는 흥분이 가득하다. 그러면서도 이 분야의 복잡성과 깊이를 전혀 손상하지 않았다. 이 책은 교수와 학생이 모두 반기고 즐길 책이다.

— 매사추세츠대학교 애머스트 캠퍼스의 슐로모 질버스틴 교수

 

러셀과 노빅의 제1판에 대한 나의 반응은 ‘지금까지 나온 최고의 책이긴 하지만 더 나은 책을 쓰는 게 불가능하지는 않겠다’였다. 제2판에 대한 반응은 ‘그 누구도 이보다 나은 인공지능 교과서를 쓰지는 못할 것이다’였다. 이 서평을 위해 제3판을 자세히 읽고 나니 그런 생각이 다시 확실해졌다. 이 책은 《The Feynman Lectures on Physics》(파인만의 물리학 강의) 수준의, 놀랄 만큼 깊고 넓은 훌륭한 교과서다. 그리고 이 책이 단지 인공지능 강좌를 위한 교재인 것은 아니다. 이 책은 합리적 사고와 행동의 이론에 관한 미증유의 개괄서이다.

— 뉴욕대학교의 어니 데이비스 교수

 

놀라운 성취이자 진정으로 아름다운 책!

— 렌셀러 폴리테크닉대학교의 셀머 브링스조드 교수

 

지은이 소개

스튜어트 러셀(Stuart Russell)
스튜어트 러셀은 현재 버클리 대학교의 컴퓨터과학과 교수이자 Center for Intelligent Systems의 책임자, 그리고 공학 스미스–자데 석좌교수(Smith–Zadeh Chair)이다. 또한, 인공지능의 다양한 주제에 관해 300편이 넘는 논문을 발표했으며, 그가 쓴 다른 책으로는 《The Use of Knowledge in Analogy and Induction》과 《Do the Right Thing: Studies in Limited Rationality》, 그리고 《Human Compatible: Artificial Intelligence and the Problem of Control》이 있다.

 

피터 노빅(Peter Norvig)
피터 노빅은 현재 구글의 연구실장이며, 2002년에서 2005년까지 핵심 웹 검색 엔진 개발을 이끌었다. 전에 NASA Ames Research Center의 계산 과학 분과장으로서 NASA의 인공지능 및 로봇공학 연구와 개발을 감독했다. 서던 캘리포니아 대학교의 교수였으며, 버클리 대학교와 스탠퍼드 대학교의 연구교수단 일원이었다. 그의 다른 책으로는 《Paradigms of AI Programming: Case Studies in Common Lisp》와 《Verbmobil: A Translation System for Face–to–Face Dialog》, 그리고 《Intelligent Help Systems for UNIX》가 있다.

 

두 저자는 2016 AAAI(American Association for Artifi cial Intelligence)/EAAI(Educational Advances in Artificial Intelligence)의 제1회 우수교육자(Outstanding Educator) 상을 공동 수상했다.

 

옮긴이 소개

류광

커누스 교수의 《컴퓨터 프로그래밍의 예술》 시리즈(한빛미디어)를 포함하여 80여 종의 다양한 IT 전문서를 번역한 전문 번역가이다. 본서 외에 《인공지능: 현대적 접근방식 제3판》(제이펍, 2016), 《심층 학습》(제이펍, 2018), 《신경망과 심층 학습》(제이펍, 2019), 《파이썬으로 배우는 자연어 처리 인 액션》(제이펍, 2020), 《심층 강화학습 인 액션》(제이펍, 2020) 같은 인공지능 관련 서적을 번역했다.

 

차례

PART I 인공지능

CHAPTER 1 소개 ∙ 3

1.1 인공지능이란 무엇인가? ·············································································· 4

1.2 인공지능의 기반 학문 ··············································································· 10

1.3 인공지능의 역사 ························································································ 25

1.4 인공지능의 현황 ························································································ 38

1.5 인공지능의 위험과 혜택 ············································································ 43

‣‣ 요약 ······································································································ 47

‣‣ 참고문헌 및 역사적 참고사항 ····························································· 49

 

CHAPTER 2 지능적 에이전트 ∙ 51

2.1 에이전트와 환경 ························································································ 52

2.2 좋은 행동: 합리성 개념 ············································································ 55

2.3 환경의 본성 ······························································································· 59

2.4 에이전트의 구조 ························································································ 65

‣‣ 요약 ······································································································ 81

‣‣ 참고문헌 및 역사적 참고사항 ····························································· 82

더보기

PART II 문제 해결

CHAPTER 3 검색을 통한 문제 해결 ∙ 87

3.1 문제 해결 에이전트 ··················································································· 88

3.2 문제의 예 ··································································································· 92

3.3 검색 알고리즘들 ························································································ 97

3.4 정보 없는 검색 전략 ··············································································· 104

3.5 정보 있는 검색(발견적 검색) 전략들 ····················································· 114

3.6 발견적 함수 ······························································································ 130

‣‣ 요약 ···································································································· 140

‣‣ 참고문헌 및 역사적 참고사항 ··························································· 141

 

CHAPTER 4 복잡한 환경의 검색 ∙ 147

4.1 국소 검색과 최적화 문제 ········································································ 147

4.2 연속 공간의 국소 검색 ············································································ 157

4.3 비결정론적 동작들을 수반한 검색 ·························································· 161

4.4 부분 관측 가능 환경의 검색 ··································································· 167

4.5 온라인 검색 에이전트와 미지 환경 ························································ 177

‣‣ 요약 ···································································································· 185

‣‣ 참고문헌 및 역사적 참고사항 ··························································· 186

 

CHAPTER 5 대립 검색과 게임 ∙ 191

5.1 게임 이론 ································································································· 191

5.2 게임의 최적 결정 ····················································································· 194

5.3 발견적 알파베타 트리 검색 ····································································· 203

5.4 몬테카를로 트리 검색 ·············································································· 210

5.5 확률적 게임 ······························································································ 214

5.6 부분 관측 가능 게임 ··············································································· 218

5.7 게임 검색 알고리즘들의 한계 ································································· 224

‣‣ 요약 ···································································································· 226

‣‣ 참고문헌 및 역사적 참고사항 ························································· 227

 

CHAPTER 6 제약 충족 문제 ∙ 235

6.1 제약 충족 문제의 정의 ············································································ 236

6.2 제약 전파: CSP의 추론 ·········································································· 242

6.3 CSP를 위한 역추적 검색 ······································································· 250

6.4 CSP를 위한 국소 검색 ··········································································· 257

6.5 문제의 구조 ······························································································ 259

‣‣ 요약 ···································································································· 265

‣‣ 참고문헌 및 역사적 참고사항 ··························································· 266

 

PART III 지식, 추론, 계획 수립

CHAPTER 7 논리적 에이전트 ∙ 273

7.1 지식 기반 에이전트 ················································································· 274

7.2 웜퍼스 세계 ······························································································ 276

7.3 논리 ·········································································································· 280

7.4 명제 논리: 아주 간단한 논리 ································································· 284

7.5 명제 정리 증명 ························································································ 291

7.6 효과적인 명제 모형 점검 ········································································ 304

7.7 명제 논리에 기초한 에이전트 ································································· 310

‣‣ 요약 ···································································································· 322

‣‣ 참고문헌 및 역사적 참고사항 ··························································· 323

 

CHAPTER 8 1차 논리 ∙ 327

8.1 표현의 재고찰 ·························································································· 327

8.2 1차 논리의 구문과 의미론 ······································································· 333

8.3 1차 논리의 활용 ······················································································· 346

8.4 1차 논리의 지식 공학 ·············································································· 354

‣‣ 요약 ···································································································· 361

‣‣ 참고문헌 및 역사적 참고사항 ··························································· 362

 

CHAPTER 9 1차 논리의 추론 ∙ 365

9.1 명제 추론 대 1차 추론 ············································································ 365

9.2 단일화와 1차 추론 ··················································································· 368

9.3 순방향 연쇄 ······························································································ 374

9.4 역방향 연쇄 ······························································································ 382

9.5 분해 ·········································································································· 389

‣‣ 요약 ···································································································· 403

‣‣ 참고문헌 및 역사적 참고사항 ··························································· 404

 

CHAPTER 10 지식 표현 ∙ 409

10.1 온톨로지 공학 ························································································ 410

10.2 범주와 객체 ···························································································· 413

10.3 사건 ········································································································ 420

10.4 정신적 객체와 양상 논리 ······································································ 425

10.5 범주 추론 시스템 ··················································································· 429

10.6 기본 정보를 이용한 추론 ······································································ 434

‣‣ 요약 ·································································································· 440

‣‣ 참고문헌 및 역사적 참고사항 ························································· 441

 

CHAPTER 11 자동 계획 수립 ∙ 449

11.1 고전적 계획 수립의 정의 ······································································ 450

11.2 고전적 계획 수립을 위한 알고리즘들 ··················································· 455

11.3 계획 수립을 위한 발견적 함수 ····························································· 460

11.4 위계적 계획 수립 ··················································································· 465

11.5 비결정론적 정의역에서의 계획 수립과 실행 ········································ 476

11.6 시간, 일정, 자원 ···················································································· 488

11.7 계획 수립 접근방식들의 분석 ······························································· 493

‣‣ 요약 ·································································································· 494

‣‣ 참고문헌 및 역사적 참고사항 ························································· 495

 

PART IV 불확실한 지식과 추론

CHAPTER 12 불확실성의 정량화 ∙ 505

12.1 불확실성하에서의 행동 ·········································································· 505

12.2 기본적인 확률 표기법 ············································································ 510

12.3 완전 결합 분포를 이용한 추론 ····························································· 518

12.4 독립성 ····································································································· 522

12.5 베이즈 규칙과 그 용법 ·········································································· 523

12.6 단순 베이즈 모형 ··················································································· 528

12.7 웜퍼스 세계의 재고찰 ············································································ 530

‣‣ 요약 ·································································································· 534

‣‣ 참고문헌 및 역사적 참고사항 ························································· 535

 

CHAPTER 13 확률적 추론 ∙ 539

13.1 불확실한 문제 영역의 지식 표현 ·························································· 539

13.2 베이즈망의 의미론 ················································································· 542

13.3 베이즈망의 정확 추론 ············································································ 558

13.4 베이즈망의 근사 추론 ············································································ 568

13.5 인과망 ····································································································· 585

‣‣ 요약 ·································································································· 591

‣‣ 참고문헌 및 역사적 참고사항 ························································· 591

 

CHAPTER 14 시간에 따른 확률적 추론 ∙ 599

14.1 시간과 불확실성 ····················································································· 600

14.2 시간적 모형의 추론 ··············································································· 605

14.3 은닉 마르코프 모형 ··············································································· 615

14.4 칼만 필터 ······························································································· 622

14.5 동적 베이즈망 ························································································ 630

‣‣ 요약 ·································································································· 643

‣‣ 참고문헌 및 역사적 참고사항 ························································· 644

 

CHAPTER 15 확률적 프로그래밍 ∙ 647

15.1 관계 확률 모형 ······················································································ 648

15.2 열린 모집단 확률 모형 ·········································································· 656

15.3 복잡한 세계의 추적 ··············································································· 665

15.4 확률 모형으로서의 프로그램 ································································· 670

‣‣ 요약 ·································································································· 676

‣‣ 참고문헌 및 역사적 참고사항 ························································· 676

 

CHAPTER 16 간단한 의사결정 ∙ 683

16.1 불확실성하에서의 믿음과 욕구의 결합 ················································· 684

16.2 효용이론의 기초 ····················································································· 685

16.3 효용 함수 ······························································································· 689

16.4 다중 특성 효용 함수 ············································································· 699

16.5 의사결정망 ······························································································ 705

16.6 정보의 가치 ···························································································· 708

16.7 미지의 선호도 ························································································ 716

‣‣ 요약 ·································································································· 720

‣‣ 참고문헌 및 역사적 참고사항 ························································· 721

 

CHAPTER 17 복잡한 의사결정 ∙ 727

17.1 순차적 의사결정 문제 ············································································ 727

17.2 MDP를 위한 알고리즘들 ······································································· 740

17.3 강도 문제 ······························································································· 750

17.4 부분 관측 가능 MDP ············································································ 759

17.5 POMDP를 푸는 알고리즘 ····································································· 762

‣‣ 요약 ·································································································· 768

‣‣ 참고문헌 및 역사적 참고사항 ························································· 769

 

CHAPTER 18 다중 에이전트 의사결정 ∙ 775

18.1 다중 에이전트 환경의 특징 ··································································· 775

18.2 비협력 게임 이론 ··················································································· 783

18.3 협력 게임 이론 ······················································································ 809

18.4 집합적 의사결정 ····················································································· 818

‣‣ 요약 ·································································································· 835

‣‣ 참고문헌 및 역사적 참고사항 ························································· 836

 

• 찾아보기 ·················································· 843

 

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