語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
A guided tour of artificial intellig...
~
Marquis, Pierre.
A guided tour of artificial intelligence research.Volume I,Knowledge representation, reasoning and learning
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
A guided tour of artificial intelligence research.edited by Pierre Marquis, Odile Papini, Henri Prade.
其他題名:
Knowledge representation, reasoning and learning
其他作者:
Marquis, Pierre.
出版者:
Cham :Springer International Publishing :2020.
面頁冊數:
xv, 803 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
Artificial intelligence.
電子資源:
https://doi.org/10.1007/978-3-030-06164-7
ISBN:
9783030061647$q(electronic bk.)
A guided tour of artificial intelligence research.Volume I,Knowledge representation, reasoning and learning
A guided tour of artificial intelligence research.
Volume I,Knowledge representation, reasoning and learning[electronic resource] /Knowledge representation, reasoning and learningedited by Pierre Marquis, Odile Papini, Henri Prade. - Cham :Springer International Publishing :2020. - xv, 803 p. :ill., digital ;24 cm.
From the content: Elements for a History of Artificial Intelligence -- Knowledge Representation: Modalities, Conditionals, and Nonmonotonic Reasoning -- Representations of Uncertainty in Artificial Intelligence: Probability and Possibility.
The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI) Implementing reasoning or decision making processes requires an appropriate representation of the pieces of information to be exploited. This first volume starts with a historical chapter sketching the slow emergence of building blocks of AI along centuries. Then the volume provides an organized overview of different logical, numerical, or graphical representation formalisms able to handle incomplete information, rules having exceptions, probabilistic and possibilistic uncertainty (and beyond), as well as taxonomies, time, space, preferences, norms, causality, and even trust and emotions among agents. Different types of reasoning, beyond classical deduction, are surveyed including nonmonotonic reasoning, belief revision, updating, information fusion, reasoning based on similarity (case-based, interpolative, or analogical), as well as reasoning about actions, reasoning about ontologies (description logics), argumentation, and negotiation or persuasion between agents. Three chapters deal with decision making, be it multiple criteria, collective, or under uncertainty. Two chapters cover statistical computational learning and reinforcement learning (other machine learning topics are covered in Volume 2) Chapters on diagnosis and supervision, validation and explanation, and knowledge base acquisition complete the volume.
ISBN: 9783030061647$q(electronic bk.)
Standard No.: 10.1007/978-3-030-06164-7doiSubjects--Topical Terms:
194058
Artificial intelligence.
LC Class. No.: Q335 / .G853 2020
Dewey Class. No.: 006.3
A guided tour of artificial intelligence research.Volume I,Knowledge representation, reasoning and learning
LDR
:03518nmm a2200337 a 4500
001
579754
003
DE-He213
005
20201005140256.0
006
m
007
cr
008
201229s2020
020
$a
9783030061647$q(electronic bk.)
020
$a
9783030061630$q(paper)
024
7
$a
10.1007/978-3-030-06164-7
$2
doi
035
$a
978-3-030-06164-7
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
Q335
$b
.G853 2020
072
7
$a
UYQ
$2
bicssc
072
7
$a
TEC009000
$2
bisacsh
072
7
$a
UYQ
$2
thema
082
0 4
$a
006.3
$2
23
090
$a
Q335
$b
.G946 2020
245
0 2
$a
A guided tour of artificial intelligence research.
$n
Volume I,
$p
Knowledge representation, reasoning and learning
$h
[electronic resource] /
$c
edited by Pierre Marquis, Odile Papini, Henri Prade.
246
3 0
$a
Knowledge representation, reasoning and learning
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2020.
300
$a
xv, 803 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
From the content: Elements for a History of Artificial Intelligence -- Knowledge Representation: Modalities, Conditionals, and Nonmonotonic Reasoning -- Representations of Uncertainty in Artificial Intelligence: Probability and Possibility.
520
$a
The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI) Implementing reasoning or decision making processes requires an appropriate representation of the pieces of information to be exploited. This first volume starts with a historical chapter sketching the slow emergence of building blocks of AI along centuries. Then the volume provides an organized overview of different logical, numerical, or graphical representation formalisms able to handle incomplete information, rules having exceptions, probabilistic and possibilistic uncertainty (and beyond), as well as taxonomies, time, space, preferences, norms, causality, and even trust and emotions among agents. Different types of reasoning, beyond classical deduction, are surveyed including nonmonotonic reasoning, belief revision, updating, information fusion, reasoning based on similarity (case-based, interpolative, or analogical), as well as reasoning about actions, reasoning about ontologies (description logics), argumentation, and negotiation or persuasion between agents. Three chapters deal with decision making, be it multiple criteria, collective, or under uncertainty. Two chapters cover statistical computational learning and reinforcement learning (other machine learning topics are covered in Volume 2) Chapters on diagnosis and supervision, validation and explanation, and knowledge base acquisition complete the volume.
650
0
$a
Artificial intelligence.
$3
194058
650
1 4
$a
Computational Intelligence.
$3
338479
650
2 4
$a
Artificial Intelligence.
$3
212515
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
275288
700
1
$a
Marquis, Pierre.
$3
869201
700
1
$a
Papini, Odile.
$3
787354
700
1
$a
Prade, Henri.
$3
485036
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer eBooks
856
4 0
$u
https://doi.org/10.1007/978-3-030-06164-7
950
$a
Intelligent Technologies and Robotics (Springer-42732)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
000000184340
電子館藏
1圖書
電子書
EB Q335 .G946 2020 2020
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
https://doi.org/10.1007/978-3-030-06164-7
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入