語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Complex adaptive systems = views fro...
~
Hadzikadic, Mirsad.
Complex adaptive systems = views from the physical, natural, and social sciences /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Complex adaptive systems/ edited by Ted Carmichael, Andrew J. Collins, Mirsad Hadzikadic.
其他題名:
views from the physical, natural, and social sciences /
其他作者:
Carmichael, Ted.
出版者:
Cham :Springer International Publishing : : 2019.,
面頁冊數:
viii, 250 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:
Springer eBooks
標題:
Swarm intelligence. -
電子資源:
https://doi.org/10.1007/978-3-030-20309-2
ISBN:
9783030203092
Complex adaptive systems = views from the physical, natural, and social sciences /
Complex adaptive systems
views from the physical, natural, and social sciences /[electronic resource] :edited by Ted Carmichael, Andrew J. Collins, Mirsad Hadzikadic. - Cham :Springer International Publishing :2019. - viii, 250 p. :ill. (some col.), digital ;24 cm. - Springer complexity. - Springer complexity..
The Fundamentals of Complex Adaptive Systems -- A Cognitive-Consistency Based Model of Population Wide Attitude Change -- An Application of Agent Based Social Modeling in the DoD -- Agent Based Behavior Precursor Model of Insider IT Sabotage -- Formal Measures of Dynamical Properties: Tipping Points, Robustness, and Sustainability -- Identifying Unexpected Behaviors of Agent-based Models through Spatial Plots and Heat Maps -- Simulating the Ridesharing Economy: The Individual Agent Metro-Washington Area Ridesharing Model (IAMWARM) -- Stigmergy for Biological Spatial Modeling -- Strategic group formation in the El Farol bar problem -- SwarmFSTaxis: Borrowing a Swarm Communication Mechanism from Fireflies and Slime Mold -- Teaching Complexity as Transdisciplinarity.
This book emerged out of international conferences organized as part of the AAAI Fall Symposia series, and the Swarmfest 2017 conference. It brings together researchers from diverse fields studying these complex systems using CAS and agent-based modeling tools and techniques. In the past, the knowledge gained in each domain has largely remained exclusive to that domain. By bringing together scholars who study these phenomena, the book takes knowledge from one domain to provide insight into others. Most interesting phenomena in natural and social systems include constant transitions and oscillations among their various phases - wars, companies, societies, markets, and humans rarely stay in a stable, predictable state for long. Randomness, power laws, and human behavior ensure that the future is both unknown and challenging. How do events unfold? When do they take hold? Why do some initial events cause an avalanche while others do not? What characterizes these events? What are the thresholds that differentiate a sea change from a non-event? Complex adaptive systems (CAS) have proven to be a powerful tool for exploring these and other related phenomena. The authors characterize a general CAS model as having a large number of self-similar agents that: 1) utilize one or more levels of feedback; 2) exhibit emergent properties and self-organization; and 3) produce non-linear dynamic behavior. Advances in modeling and computing technology have led not only to a deeper understanding of complex systems in many areas, but they have also raised the possibility that similar fundamental principles may be at work across these systems, even though the underlying principles may manifest themselves differently.
ISBN: 9783030203092
Standard No.: 10.1007/978-3-030-20309-2doiSubjects--Topical Terms:
560714
Swarm intelligence.
LC Class. No.: QA76.76.I58 / C66 2019
Dewey Class. No.: 006.30285436
Complex adaptive systems = views from the physical, natural, and social sciences /
LDR
:03633nam a2200349 a 4500
001
941198
003
DE-He213
005
20190614124617.0
006
m d
007
cr nn 008maaau
008
200417s2019 gw s 0 eng d
020
$a
9783030203092
$q
(electronic bk.)
020
$a
9783030203078
$q
(paper)
024
7
$a
10.1007/978-3-030-20309-2
$2
doi
035
$a
978-3-030-20309-2
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.76.I58
$b
C66 2019
072
7
$a
GPFC
$2
bicssc
072
7
$a
TEC000000
$2
bisacsh
072
7
$a
GPFC
$2
thema
082
0 4
$a
006.30285436
$2
23
090
$a
QA76.76.I58
$b
C737 2019
245
0 0
$a
Complex adaptive systems
$h
[electronic resource] :
$b
views from the physical, natural, and social sciences /
$c
edited by Ted Carmichael, Andrew J. Collins, Mirsad Hadzikadic.
260
$a
Cham :
$c
2019.
$b
Springer International Publishing :
$b
Imprint: Springer,
300
$a
viii, 250 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Springer complexity
490
1
$a
Understanding complex systems
505
0
$a
The Fundamentals of Complex Adaptive Systems -- A Cognitive-Consistency Based Model of Population Wide Attitude Change -- An Application of Agent Based Social Modeling in the DoD -- Agent Based Behavior Precursor Model of Insider IT Sabotage -- Formal Measures of Dynamical Properties: Tipping Points, Robustness, and Sustainability -- Identifying Unexpected Behaviors of Agent-based Models through Spatial Plots and Heat Maps -- Simulating the Ridesharing Economy: The Individual Agent Metro-Washington Area Ridesharing Model (IAMWARM) -- Stigmergy for Biological Spatial Modeling -- Strategic group formation in the El Farol bar problem -- SwarmFSTaxis: Borrowing a Swarm Communication Mechanism from Fireflies and Slime Mold -- Teaching Complexity as Transdisciplinarity.
520
$a
This book emerged out of international conferences organized as part of the AAAI Fall Symposia series, and the Swarmfest 2017 conference. It brings together researchers from diverse fields studying these complex systems using CAS and agent-based modeling tools and techniques. In the past, the knowledge gained in each domain has largely remained exclusive to that domain. By bringing together scholars who study these phenomena, the book takes knowledge from one domain to provide insight into others. Most interesting phenomena in natural and social systems include constant transitions and oscillations among their various phases - wars, companies, societies, markets, and humans rarely stay in a stable, predictable state for long. Randomness, power laws, and human behavior ensure that the future is both unknown and challenging. How do events unfold? When do they take hold? Why do some initial events cause an avalanche while others do not? What characterizes these events? What are the thresholds that differentiate a sea change from a non-event? Complex adaptive systems (CAS) have proven to be a powerful tool for exploring these and other related phenomena. The authors characterize a general CAS model as having a large number of self-similar agents that: 1) utilize one or more levels of feedback; 2) exhibit emergent properties and self-organization; and 3) produce non-linear dynamic behavior. Advances in modeling and computing technology have led not only to a deeper understanding of complex systems in many areas, but they have also raised the possibility that similar fundamental principles may be at work across these systems, even though the underlying principles may manifest themselves differently.
650
0
$a
Swarm intelligence.
$3
560714
650
0
$a
Intelligent agents (Computer software)
$3
558701
650
0
$a
Computational complexity.
$3
527777
650
1 4
$a
Complexity.
$3
669595
650
2 4
$a
Applications of Nonlinear Dynamics and Chaos Theory.
$3
1113607
650
2 4
$a
Applications of Graph Theory and Complex Networks.
$3
1113468
700
1
$a
Carmichael, Ted.
$3
1228300
700
1
$a
Collins, Andrew J.
$3
1228301
700
1
$a
Hadzikadic, Mirsad.
$3
1077791
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
830
0
$a
Springer complexity.
$3
1066478
830
0
$a
Understanding complex systems.
$3
881607
856
4 0
$u
https://doi.org/10.1007/978-3-030-20309-2
950
$a
Engineering (Springer-11647)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入