크레마클럽

PART I 인공지능CHAPTER 1 소개 31.1 인공지능이란 무엇인가? ·············································································· 41.2 인공지능의 기반 학문 ··············································································· 101.3 인공지능의 역사 ························································································ 251.4 인공지능의 현황 ························································································ 381.5 인공지능의 위험과 혜택 ············································································ 43 요약 ······································································································ 47 참고문헌 및 역사적 참고사항 ····························································· 49CHAPTER 2 지능적 에이전트 512.1 에이전트와 환경 ························································································ 522.2 좋은 행동: 합리성 개념 ············································································ 552.3 환경의 본성 ······························································································· 592.4 에이전트의 구조 ························································································ 65 요약 ······································································································ 81 참고문헌 및 역사적 참고사항 ····························································· 82PART II 문제 해결CHAPTER 3 검색을 통한 문제 해결 873.1 문제 해결 에이전트 ··················································································· 883.2 문제의 예 ··································································································· 923.3 검색 알고리즘들 ························································································ 973.4 정보 없는 검색 전략 ··············································································· 1043.5 정보 있는 검색(발견적 검색) 전략들 ····················································· 1143.6 발견적 함수 ······························································································ 130 요약 ···································································································· 140 참고문헌 및 역사적 참고사항 ··························································· 141CHAPTER 4 복잡한 환경의 검색 1474.1 국소 검색과 최적화 문제 ········································································ 1474.2 연속 공간의 국소 검색 ············································································ 1574.3 비결정론적 동작들을 수반한 검색 ·························································· 1614.4 부분 관측 가능 환경의 검색 ··································································· 1674.5 온라인 검색 에이전트와 미지 환경 ························································ 177 요약 ···································································································· 185 참고문헌 및 역사적 참고사항 ··························································· 186CHAPTER 5 대립 검색과 게임 1915.1 게임 이론 ································································································· 1915.2 게임의 최적 결정 ····················································································· 1945.3 발견적 알파베타 트리 검색 ····································································· 2035.4 몬테카를로 트리 검색 ·············································································· 2105.5 확률적 게임 ······························································································ 2145.6 부분 관측 가능 게임 ··············································································· 2185.7 게임 검색 알고리즘들의 한계 ································································· 224 요약 ···································································································· 226 참고문헌 및 역사적 참고사항 ························································· 227CHAPTER 6 제약 충족 문제 2356.1 제약 충족 문제의 정의 ············································································ 2366.2 제약 전파: CSP의 추론 ·········································································· 2426.3 CSP를 위한 역추적 검색 ······································································· 2506.4 CSP를 위한 국소 검색 ··········································································· 2576.5 문제의 구조 ······························································································ 259 요약 ···································································································· 265 참고문헌 및 역사적 참고사항 ··························································· 266PART III 지식, 추론, 계획 수립CHAPTER 7 논리적 에이전트 2737.1 지식 기반 에이전트 ················································································· 2747.2 웜퍼스 세계 ······························································································ 2767.3 논리 ·········································································································· 2807.4 명제 논리: 아주 간단한 논리 ································································· 2847.5 명제 정리 증명 ························································································ 2917.6 효과적인 명제 모형 점검 ········································································ 3047.7 명제 논리에 기초한 에이전트 ································································· 310 요약 ···································································································· 322 참고문헌 및 역사적 참고사항 ··························································· 323CHAPTER 8 1차 논리 3278.1 표현의 재고찰 ·························································································· 3278.2 1차 논리의 구문과 의미론 ······································································· 3338.3 1차 논리의 활용 ······················································································· 3468.4 1차 논리의 지식 공학 ·············································································· 354 요약 ···································································································· 361 참고문헌 및 역사적 참고사항 ··························································· 362CHAPTER 9 1차 논리의 추론 3659.1 명제 추론 대 1차 추론 ············································································ 3659.2 단일화와 1차 추론 ··················································································· 3689.3 순방향 연쇄 ······························································································ 3749.4 역방향 연쇄 ······························································································ 3829.5 분해 ·········································································································· 389 요약 ···································································································· 403 참고문헌 및 역사적 참고사항 ··························································· 404CHAPTER 10 지식 표현 40910.1 온톨로지 공학 ························································································ 41010.2 범주와 객체 ···························································································· 41310.3 사건 ········································································································ 42010.4 정신적 객체와 양상 논리 ······································································ 42510.5 범주 추론 시스템 ··················································································· 42910.6 기본 정보를 이용한 추론 ······································································ 434 요약 ·································································································· 440 참고문헌 및 역사적 참고사항 ························································· 441CHAPTER 11 자동 계획 수립 44911.1 고전적 계획 수립의 정의 ······································································ 45011.2 고전적 계획 수립을 위한 알고리즘들 ··················································· 45511.3 계획 수립을 위한 발견적 함수 ····························································· 46011.4 위계적 계획 수립 ··················································································· 46511.5 비결정론적 정의역에서의 계획 수립과 실행 ········································ 47611.6 시간, 일정, 자원 ···················································································· 48811.7 계획 수립 접근방식들의 분석 ······························································· 493 요약 ·································································································· 494 참고문헌 및 역사적 참고사항 ························································· 495PART IV 불확실한 지식과 추론CHAPTER 12 불확실성의 정량화 50512.1 불확실성하에서의 행동 ·········································································· 50512.2 기본적인 확률 표기법 ············································································ 51012.3 완전 결합 분포를 이용한 추론 ····························································· 51812.4 독립성 ····································································································· 52212.5 베이즈 규칙과 그 용법 ·········································································· 52312.6 단순 베이즈 모형 ··················································································· 52812.7 웜퍼스 세계의 재고찰 ············································································ 530 요약 ·································································································· 534 참고문헌 및 역사적 참고사항 ························································· 535CHAPTER 13 확률적 추론 53913.1 불확실한 문제 영역의 지식 표현 ·························································· 53913.2 베이즈망의 의미론 ················································································· 54213.3 베이즈망의 정확 추론 ············································································ 55813.4 베이즈망의 근사 추론 ············································································ 56813.5 인과망 ····································································································· 585 요약 ·································································································· 591 참고문헌 및 역사적 참고사항 ························································· 591CHAPTER 14 시간에 따른 확률적 추론 59914.1 시간과 불확실성 ····················································································· 60014.2 시간적 모형의 추론 ··············································································· 60514.3 은닉 마르코프 모형 ··············································································· 61514.4 칼만 필터 ······························································································· 62214.5 동적 베이즈망 ························································································ 630 요약 ·································································································· 643 참고문헌 및 역사적 참고사항 ························································· 644CHAPTER 15 확률적 프로그래밍 64715.1 관계 확률 모형 ······················································································ 64815.2 열린 모집단 확률 모형 ·········································································· 65615.3 복잡한 세계의 추적 ··············································································· 66515.4 확률 모형으로서의 프로그램 ································································· 670 요약 ·································································································· 676 참고문헌 및 역사적 참고사항 ························································· 676CHAPTER 16 간단한 의사결정 68316.1 불확실성하에서의 믿음과 욕구의 결합 ················································· 68416.2 효용이론의 기초 ····················································································· 68516.3 효용 함수 ······························································································· 68916.4 다중 특성 효용 함수 ············································································· 69916.5 의사결정망 ······························································································ 70516.6 정보의 가치 ···························································································· 70816.7 미지의 선호도 ························································································ 716 요약 ·································································································· 720 참고문헌 및 역사적 참고사항 ························································· 721CHAPTER 17 복잡한 의사결정 72717.1 순차적 의사결정 문제 ············································································ 72717.2 MDP를 위한 알고리즘들 ······································································· 74017.3 강도 문제 ······························································································· 75017.4 부분 관측 가능 MDP ············································································ 75917.5 POMDP를 푸는 알고리즘 ····································································· 762 요약 ·································································································· 768 참고문헌 및 역사적 참고사항 ························································· 769CHAPTER 18 다중 에이전트 의사결정 77518.1 다중 에이전트 환경의 특징 ··································································· 77518.2 비협력 게임 이론 ··················································································· 78318.3 협력 게임 이론 ······················································································ 80918.4 집합적 의사결정 ····················································································· 818 요약 ·································································································· 835 참고문헌 및 역사적 참고사항 ························································· 836 찾아보기 ·················································· 843

펼쳐보기접어보기

상세 이미지

저자 소개 (3명)

저 : 피터 노빅 (Peter Norvig)

관심작가 알림신청

구글의 연구실장이며, 2002년에서 2005년까지 핵심 웹 검색 엔진 개발을 이끌었다. 전에는 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 He... 구글의 연구실장이며, 2002년에서 2005년까지 핵심 웹 검색 엔진 개발을 이끌었다. 전에는 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.

펼쳐보기접어보기

저 : 스튜어트 러셀 (Stuart Russell)

관심작가 알림신청

버클리에 있는 캘리포니아대학교 컴퓨터과학 교수이자 공학 부문 스미스자데이 석좌교수. 옥스퍼드대학교 웨덤 칼리지에서 물리학을 공부하고 스탠퍼드대학교에서 컴퓨터과학으로 박사학위를 받았다. 기계 학습, 확률론적 추론, 실시간 의사 결정, 계산 생리학 및 철학적 기초를 포함한 인공지능의 광범위한 주제를 놓고 연구했고, 지금은 자율무기의 위협, 인공지능의 장기적 미래 및 인류와의 관계 등에도 관심을 두고 있다. 미국 인공지능협회, 컴퓨터학회, 미국과학진흥협회 회원이며, 세계경제포럼의 AI와 로봇학 위원회 부의장, 유엔 군축 문제 고문도 맡고 있다. 2016 서울디지털포럼, 2020 서울포... 버클리에 있는 캘리포니아대학교 컴퓨터과학 교수이자 공학 부문 스미스자데이 석좌교수. 옥스퍼드대학교 웨덤 칼리지에서 물리학을 공부하고 스탠퍼드대학교에서 컴퓨터과학으로 박사학위를 받았다. 기계 학습, 확률론적 추론, 실시간 의사 결정, 계산 생리학 및 철학적 기초를 포함한 인공지능의 광범위한 주제를 놓고 연구했고, 지금은 자율무기의 위협, 인공지능의 장기적 미래 및 인류와의 관계 등에도 관심을 두고 있다. 미국 인공지능협회, 컴퓨터학회, 미국과학진흥협회 회원이며, 세계경제포럼의 AI와 로봇학 위원회 부의장, 유엔 군축 문제 고문도 맡고 있다. 2016 서울디지털포럼, 2020 서울포럼 등에서 강연하기도 했다.

구글 리서치 디렉터 피터 노빅과 함께 『인공지능: 현대적 접근방식』(1995)을 썼다. AI 분야의 결정판 교과서로 널리 인정받고 있는 『인공지능』(현재 4판)은 13개 언어로 번역되어 118개국, 1,500여 대학에서 교재로 사용되고 있다. 2016년에는 UC 버클리를 중심으로 여러 대학과 기관이 협력하는 연구기관 ‘휴먼컴패터블 AI센터’를 설립하여 AI 연구의 일반적인 추진 방향을 증명 가능하게 유익한 AI 시스템 쪽으로 재설정하는 데 필요한 개념적·기술적 도구를 개발해왔고, 그 결과물을 『어떻게 인간과 공존하는 인공지능을 만들 것인가: AI와 통제 문제』에 담았다.

펼쳐보기접어보기

역 : 류광

관심작가 알림신청

도널드 커누스 교수의 《컴퓨터 프로그래밍의 예술》 시리즈를 비롯해 다양한 IT 전문서를 번역한 전문 번역가이다. 생성형 AI 관련 번역서로는 《마스터링 트랜스포머》《실전! RAG 기반 생성형 AI 개발》《LLM 인 프로덕션》《AI 에이전트 인 액션》 등이 있다. 개인 웹사이트 류광의 번역 이야기(https://occamsrazr.net)와 IT 및 게임 개발 정보 공유 사이트 GpgStudy.com(https://gpgstudy.com)을 운영한다 도널드 커누스 교수의 《컴퓨터 프로그래밍의 예술》 시리즈를 비롯해 다양한 IT 전문서를 번역한 전문 번역가이다. 생성형 AI 관련 번역서로는 《마스터링 트랜스포머》《실전! RAG 기반 생성형 AI 개발》《LLM 인 프로덕션》《AI 에이전트 인 액션》 등이 있다. 개인 웹사이트 류광의 번역 이야기(https://occamsrazr.net)와 IT 및 게임 개발 정보 공유 사이트 GpgStudy.com(https://gpgstudy.com)을 운영한다

크레마클럽에서 볼 수 있는 작가의 다른 책

출판사 리뷰

2010년대 인공신경망의 부활과 심층학습의 눈부신 성과를 반영한 인공지능 연구의 결정판!2016년에 나온 제3판 번역서(2009년에 출간된 원서 3판을 번역)는 최신 연구 반영에 한계가 있었으나, 이번 제4판 번역서는 최근 성과(자연어 이해, 로봇공학, 컴퓨터 시각에 심층학습이 끼친 영향, 강화학습을 로봇공학에 적용하는 방법, 기계학습, 인공지능 윤리 등)를 충실하게 반영한, 2020년에 출간된 원서를 옮긴 것이라 이 분야의 ‘좀 더 통합된 상’을 원하는 여러 독자의 갈증을 해소하는 데 큰 도움이 될 것입니다.전체적으로, 책의 약 25%가 완전히 새로운 내용이고 나머지 75%도 이 분야의 좀 더 통합된 상을 제시하기 위해 크게 변경되었으며, 이번 판에서 인용한 문헌의 22%는 2010년 이후에 출판된 것들입니다.제4판에서 새로운 점들□ 사람이 손으로 짜는 지식 공학보다는 기계학습에 좀 더 무게를 실었다. 기계학습은 가용 데이터와 컴퓨팅 자원이 증가하고 새로운 알고리즘들이 등장한 덕분에 큰 성공을 거두고 있다.□ 심층학습, 확률적 프로그래밍, 다중 에이전트 시스템을 각각 개별적인 장(챕터)으로 두어서 좀 더 자세히 다룬다.□ 자연어 이해, 로봇공학, 컴퓨터 시각에 관한 장들을 심층학습이 끼친 영향을 반영해서 수정했다.□ 로봇공학 장에 사람과 상호작용하는 로봇에 관한 내용과 강화학습을 로봇공학에 적용하는 방법에 관한 내용이 추가되었다.□ 이전에는 인공지능의 목표를 사람이 구체적인 효용 정보(목적함수)를 제공한다는 가정하에서 기대 효용을 최대화하려는 시스템을 만드는 것이라고 정의했다. 그러나 이번 판에서는 목적함수가 고정되어 있으며 인공지능 시스템이 목적함수를 알고 있다고 가정하지 않는다. 대신, 시스템은 자신이 봉사하는 인간의 진짜 목적이 무엇인지 확실하게 알지 못할 수 있다고 가정한다. 시스템은 반드시 자신이 무엇을 최대화할 것인지를 배워야 하며, 목적에 관해 불확실성이 존재하더라도 적절히 작동해야 한다.□ 인공지능이 사회에 미치는 영향을 좀 더 자세하게 다루었다. 여기에는 윤리, 공정성, 신뢰, 안정성에 관한 핵심적인 문제들을 고찰한다.□ 각 장 끝의 연습문제들을 온라인 사이트로 옮겼다. 덕분에 강사들의 요구와 이 분야 및 인공지능 관련 소프트웨어 도구의 발전에 맞게 연습문제들을 계속 추가, 갱신, 개선할 수 있게 되었다.

펼쳐보기접어보기