PACKT (406)
Text Book 교재용원서 (673)
컴퓨터공학 (819)
컴퓨터 일반도서 (555)
전기,전자공학 (710)
기계공학 (197)
재료공학 (34)
에너지공학 (65)
의용공학 (39)
생명과학 (229)
물리학 (426)
지구과학 (74)
천문학 (39)
수학 (103)
통계학 (45)
경영학 (40)
산업공학 (12)
사회복지학 (5)
심리학 (247)
교육학 (1)
화학 (5)
기타 (64)
특가할인도서 (택배비별도) (87)

> > 컴퓨터공학 > 인공지능

이미지를 클릭하시면 큰 이미지를 보실 수 있습니다.
Artificial Intelligence Foundations of Computational Agents 2nd Edition
출판사 : Cambridge University Press
저 자 : Poole
ISBN : 9781107195394
발행일 : 2017-9
도서종류 : 외국도서
발행언어 : 영어
페이지수 : 820
판매가격 : 49,000원
판매여부 : 재고확인요망
261 x 182 x 39 mm :
주문수량 : [+]수량을 1개 늘입니다 [-]수량을 1개 줄입니다

My Wish List 에 저장하기
   Artificial Intelligence Foundations of Computational Agents 2nd Edition 목차

Table of Contents

Part I. Agents in the World: What Are Agents and How Can They Be Built?:
1. Artificial intelligence and agents
2. Agent architectures and hierarchical control
Part II. Reasoning, Planning and Learning with Certainty:
3. Searching for solutions
4. Reasoning with constraints
5. Propositions and inference
6. Planning with certainty
7. Supervised machine learning
Part III. Reasoning, Learning and Acting with Uncertainty:
8. Reasoning with uncertainty
9. Planning with uncertainty
10. Learning with uncertainty
11. Multiagent systems
12. Learning to act
Part IV. Reasoning, Learning and Acting with Individuals and Relations:
13. Individuals and relations
14. Ontologies and knowledge-based systems
15. Relational planning, learning, and probabilistic reasoning
Part V. Retrospect and Prospect:
16. Retrospect and prospect
Part VI. End Matter: Appendix A. Mathematical preliminaries and notation.
   도서 상세설명   


Artificial intelligence, including machine learning, has emerged as a transformational science and engineering discipline. Artificial Intelligence: Foundations of Computational Agents presents AI using a coherent framework to study the design of intelligent computational agents. By showing how the basic approaches fit into a multidimensional design space, readers learn the fundamentals without losing sight of the bigger picture. The new edition also features expanded coverage on machine learning material, as well as on the social and ethical consequences of AI and ML. The book balances theory and experiment, showing how to link them together, and develops the science of AI together with its engineering applications. Although structured as an undergraduate and graduate textbook, the book's straightforward, self-contained style will also appeal to an audience of professionals, researchers, and independent learners. The second edition is well-supported by strong pedagogical features and online resources to enhance student comprehension.

Customer reviews

22nd Mar 2018 by Napoleonboakye1
Wow, I love this book. I read the 2010 version online and immediately recommended it to my students and scholars who were taking Ng's ML course on Coursera. It widens your horizon in terms of intelligence. It has been broken down to a layman's understanding and a researcher's intuitiveness. The way artificial intelligence and natural intelligence was explained was best to none. This newer version comes with brevity and conciseness. A must read even if you are only interested in ML

  교육용 보조자료   
작성된 교육용 보조자료가 없습니다.