Complex adaptive systems: an introduction to computational models of social life
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Princeton, NJ [u.a.]
Princeton Univ. Press
2007
|
| Schriftenreihe: | Princeton studies in complexity
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIX, 263 S. Ill., graph. Darst. |
| ISBN: | 9780691127026 0691127026 0691130965 9780691130965 |
Internformat
MARC
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| 100 | 1 | |a Miller, John H. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Complex adaptive systems |b an introduction to computational models of social life |c John H. Miller and Scott E. Page |
| 264 | 1 | |a Princeton, NJ [u.a.] |b Princeton Univ. Press |c 2007 | |
| 300 | |a XIX, 263 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Princeton studies in complexity | |
| 650 | 7 | |a Ciências sociais (modelos matemáticos) |2 larpcal | |
| 650 | 4 | |a Computermodellen | |
| 650 | 7 | |a Computermodellen |2 gtt | |
| 650 | 7 | |a Modelli matematici - applicazioni |2 sbt | |
| 650 | 4 | |a Sciences sociales - Modèles mathématiques | |
| 650 | 7 | |a Scienze sociali - modelli matematici |2 sbt | |
| 650 | 4 | |a Sociale relaties | |
| 650 | 7 | |a Sociale relaties |2 gtt | |
| 650 | 4 | |a Systèmes sociaux - Modèles mathématiques | |
| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Sozialwissenschaften | |
| 650 | 4 | |a Social sciences |x Mathematical models | |
| 650 | 4 | |a Social systems |x Mathematical models | |
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| 700 | 1 | |a Page, Scott E. |e Verfasser |4 aut | |
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Datensatz im Suchindex
| _version_ | 1804136439999365120 |
|---|---|
| adam_text | Contents
List of Figures
xiii
List of Tables
xv
Preface
xvii
Part I Introduction
1
1
Introduction
3
2
Complexity in Social Worlds
9
2.1
The Standing Ovation Problem
10
2.2
What s the Buzz?
14
2.2.1
Stay Cool
14
2.2.2
Artad:
of f/>e
ЈШег
Bees
15
2.2.3
Averaging Out Average Behavior
16
2.3
A Tale of Two Cities
17
2.3.1
Adding Complexity
20
2.4
New Directions
26
2.5
Complex Social Worlds Redux
27
2.5.1
Questioning Complexity
27
Part II Preliminaries
33
3
Modeling
35
3.1
Models as Maps
36
3.2
A More Formal Approach to Modeling
38
3.3
Modeling Complex Systems
40
3.4
Modeling Modeling
42
4
On Emergence
44
4.1
A Theory of Emergence
46
4.2
Beyond Disorganized Complexity
48
4.2.1
Feedback and Organized Complexity
50
Part III Computational Modeling
55
5
Computation as Theory
57
5.1
Theory versus Tools
59
5.1.1
Physics Envy: A Pseudo-Freudian Analysis
62
viii
· Contents
5.2
Computation and Theory
64
5.2.1
Computation in Theory
64
5.2.2
Computation as Theory
67
5.3
Objections to Computation as Theory
68
5.3.1
Computations Build in Their Results
69
5.3.2
Computations Lack Discipline
70
5.3.3
Computational Models Are Only Approximations to
Specific Circumstances
71
5.3.4
Computational Models Are Brittle
72
5.3.5
Computational Models Are Hard to Test
73
5.3.6
Computational Models Are Hard to Understand
76
5.4
New Directions
6
6
Why Agent-Based Objects?
78
6.1
Flexibility versus Precision
78
6.2
Process Oriented
80
6.3
Adaptive Agents
81
6.4
Inherently Dynamic
83
6.5
Heterogeneous Agents and Asymmetry
84
6.6
Scalability
85
6.7
Repeatable and Recoverable
86
6.8
Constructive
86
6.9
Low Cost
87
6.10
Economic
E. coli (E. conif)
88
Part IV Models of Complex Adaptive
Social Systems
91
7
A Basic Framework
93
7.1
The Eightfold Way
93
7.1.1
Right View
94
7.1.2
Right Intention
95
7.1.3
Right Speech
96
7.1.4
Right Action
96
7.1.5
Right Livelihood
97
7.1.6
Right Effort
98
7.1.7
Right Mindfulness
100
7.1.8
Kigfcf Concentration
101
7.2
Smoke and Mirrors: The Forest Fire Model
102
7.2.1
A Simple Model of Forest Fires
102
7.2.2
Fixed, Homogeneous Rules
102
7.2.3
Homogeneous Adaptation
104
7.2.4
Heterogeneous Adaptation
105
Contents
7.2.5
Adding More Intelligence: Internal Models
107
7.2.6
Omniscient Closure
108
7.2.7
Banks
109
7.3
Eight Folding into One
110
7.4
Conclusion
113
8
Complex Adaptive Social Systems in One Dimension
114
8.1
Cellular Automata
115
8.2
Social Cellular Automata
119
8.2.1
Socially Acceptable Rules
120
8.3
Majority Rules
124
8.3.1
The Zen of Mistakes in Majority Rule
128
8.4
The Edge of Chaos
129
8.4.1
Is There an Edge?
130
8.4.2
Computation at the Edge of Chaos
137
8.4.3
The Edge of Robustness
139
9
Social Dynamics
141
9.1
A Roving Agent
141
9.2
Segregation
143
9.3
The Beach Problem
146
9.4
City Formation
151
9.5
Networks
154
9.5.1
Majority Rule and Network Structures
158
9.5.2
Schelling s Segregation Model and Network Structures
163
9.6
Self-Organized Criticality and Power Laws
165
9.6.1
The Sand Pile Model
167
9.6.2
A Minimalist Sand Pile
169
9.6.3
Fat-Tailed Avalanches
171
9.6
A Purposive Agents
175
9.6.5
The Forest Fire Model Redux
176
9.6.6
Criticality in Social Systems
177
10
Evolving Automata
178
10.1
Agent Behavior
178
10.2
Adaptation
180
10.3
A Taxonomy of
2
χ
2
Games
185
10.3.1
Methodology
187
10.3.2
Results
189
10.4
Games Theory: One Agent, Many Games
191
10.5
Evolving Communication
192
10.5.1
Results
194
10.5.2
Furthering Communication
197
10.6
The Full Monty
198
χ
· Contents
11
Some Fundamentals of Organizational Decision Making
200
11.1
Organizations and Boolean Functions
201
11.2
Some Results
203
11.3
Do Organizations Just Find Solvable Problems?
206
11.3.1
Imperfection
207
11.4
Future Directions
210
Part V Conclusions
211
12
Social Science in Between
213
12.1
Some Contributions
214
12.2
The Interest in Between
218
12.2.1
in between Simple and Strategic Behavior
219
12.2.2
in between Pairs and Infinities of Agents
221
12.2.3
In between Equilibrium and Chaos
222
12.2.4
In between Richness and Rigor
223
12.2.5
In between Anarchy and Control
225
12.3
Here Be Dragons
225
Epilogue
227
The Interest in Between
227
Social Complexity
228
The Faraway Nearby
230
Appendixes
A An Open Agenda For Complex Adaptive Social Systems
231
A.I Whither Complexity
231
A.2 What Does it Take for a System to Exhibit Complex
Behavior?
233
A.3 Is There an Objective Basis for Recognizing Emergence and
Complexity?
233
A.4 Is There a Mathematics of Complex Adaptive Social Systems?
234
A.5 What Mechanisms Exist for Tuning the Performance of
Complex Systems?
235
A.6 Do Productive Complex Systems Have Unusual Properties?
235
A.7 Do Social Systems Become More Complex over Time
236
A.8 What Makes a System Robust?
236
A.9 Causality in Complex Systems?
237
A.
10
When Does Coevolution Work?
237
A.
11
When Does Updating Matter?
238
A.
12
When Does Heterogeneity Matter?
238
Contents · xi
A.13
How Sophisticated Must Agents Be Before They Are
Interesting?
239
A.
14
What Are the Equivalence Classes of Adaptive Behavior?
240
A.
15
When Does Adaptation Lead to Optimization and
Equilibrium?
241
A.16 How Important Is Communication to Complex Adaptive
Social Systems?
242
A.17 How Do Decentralized Markets Equilibrate?
243
A.I
8
When Do Organizations Arise?
243
A.19 What Are the Origins of Social Life?
244
В
Practices for Computational Modeling
245
B.I Keep the Model Simple
246
B.2 Focus on the Science, Not the Computer
246
B.3 The Old Computer Test
247
B.4 Avoid Black Boxes
247
B.5 Nest Your Models
248
B.6 Have Tunable Dials
248
B.7 Construct Flexible Frameworks
249
B.8 Create Multiple Implementations
249
B.9 Check the Parameters
250
B.10 Document Code
250
B.ll Know the Source of Random Numbers
251
B.12 Beware of Debugging Bias
251
B.13 Write Good Code
251
B.I
4
Avoid False Precision
252
B.15 Distribute Your Code
253
B.
16
Keep a Lab Notebook
253
B.17 Prove Your Results
253
B.I
8
Reward the Right Things
254
Bibliography
255
Index
261
|
| adam_txt |
Contents
List of Figures
xiii
List of Tables
xv
Preface
xvii
Part I Introduction
1
1
Introduction
3
2
Complexity in Social Worlds
9
2.1
The Standing Ovation Problem
10
2.2
What's the Buzz?
14
2.2.1
Stay Cool
14
2.2.2
Artad:
of f/>e
ЈШег
Bees
15
2.2.3
Averaging Out Average Behavior
16
2.3
A Tale of Two Cities
17
2.3.1
Adding Complexity
20
2.4
New Directions
26
2.5
Complex Social Worlds Redux
27
2.5.1
Questioning Complexity
27
Part II Preliminaries
33
3
Modeling
35
3.1
Models as Maps
36
3.2
A More Formal Approach to Modeling
38
3.3
Modeling Complex Systems
40
3.4
Modeling Modeling
42
4
On Emergence
44
4.1
A Theory of Emergence
46
4.2
Beyond Disorganized Complexity
48
4.2.1
Feedback and Organized Complexity
50
Part III Computational Modeling
55
5
Computation as Theory
57
5.1
Theory versus Tools
59
5.1.1
Physics Envy: A Pseudo-Freudian Analysis
62
viii
· Contents
5.2
Computation and Theory
64
5.2.1
Computation in Theory
64
5.2.2
Computation as Theory
67
5.3
Objections to Computation as Theory
68
5.3.1
Computations Build in Their Results
69
5.3.2
Computations Lack Discipline
70
5.3.3
Computational Models Are Only Approximations to
Specific Circumstances
71
5.3.4
Computational Models Are Brittle
72
5.3.5
Computational Models Are Hard to Test
73
5.3.6
Computational Models Are Hard to Understand
76
5.4
New Directions
'6
6
Why Agent-Based Objects?
78
6.1
Flexibility versus Precision
78
6.2
Process Oriented
80
6.3
Adaptive Agents
81
6.4
Inherently Dynamic
83
6.5
Heterogeneous Agents and Asymmetry
84
6.6
Scalability
85
6.7
Repeatable and Recoverable
86
6.8
Constructive
86
6.9
Low Cost
87
6.10
Economic
E. coli (E. conif)
88
Part IV Models of Complex Adaptive
Social Systems
91
7
A Basic Framework
93
7.1
The Eightfold Way
93
7.1.1
Right View
94
7.1.2
Right Intention
95
7.1.3
Right Speech
96
7.1.4
Right Action
96
7.1.5
Right Livelihood
97
7.1.6
Right Effort
98
7.1.7
Right Mindfulness
100
7.1.8
Kigfcf Concentration
101
7.2
Smoke and Mirrors: The Forest Fire Model
102
7.2.1
A Simple Model of Forest Fires
102
7.2.2
Fixed, Homogeneous Rules
102
7.2.3
Homogeneous Adaptation
104
7.2.4
Heterogeneous Adaptation
105
Contents
7.2.5
Adding More Intelligence: Internal Models
107
7.2.6
Omniscient Closure
108
7.2.7
Banks
109
7.3
Eight Folding into One
110
7.4
Conclusion
113
8
Complex Adaptive Social Systems in One Dimension
114
8.1
Cellular Automata
115
8.2
Social Cellular Automata
119
8.2.1
Socially Acceptable Rules
120
8.3
Majority Rules
124
8.3.1
The Zen of Mistakes in Majority Rule
128
8.4
The Edge of Chaos
129
8.4.1
Is There an Edge?
130
8.4.2
Computation at the Edge of Chaos
137
8.4.3
The Edge of Robustness
139
9
Social Dynamics
141
9.1
A Roving Agent
141
9.2
Segregation
143
9.3
The Beach Problem
146
9.4
City Formation
151
9.5
Networks
154
9.5.1
Majority Rule and Network Structures
158
9.5.2
Schelling's Segregation Model and Network Structures
163
9.6
Self-Organized Criticality and Power Laws
165
9.6.1
The Sand Pile Model
167
9.6.2
A Minimalist Sand Pile
169
9.6.3
Fat-Tailed Avalanches
171
9.6
A Purposive Agents
175
9.6.5
The Forest Fire Model Redux
176
9.6.6
Criticality in Social Systems
177
10
Evolving Automata
178
10.1
Agent Behavior
178
10.2
Adaptation
180
10.3
A Taxonomy of
2
χ
2
Games
185
10.3.1
Methodology
187
10.3.2
Results
189
10.4
Games Theory: One Agent, Many Games
191
10.5
Evolving Communication
192
10.5.1
Results
194
10.5.2
Furthering Communication
197
10.6
The Full Monty
198
χ
· Contents
11
Some Fundamentals of Organizational Decision Making
200
11.1
Organizations and Boolean Functions
201
11.2
Some Results
203
11.3
Do Organizations Just Find Solvable Problems?
206
11.3.1
Imperfection
207
11.4
Future Directions
210
Part V Conclusions
211
12
Social Science in Between
213
12.1
Some Contributions
214
12.2
The Interest in Between
218
12.2.1
in between Simple and Strategic Behavior
219
12.2.2
in between Pairs and Infinities of Agents
221
12.2.3
In between Equilibrium and Chaos
222
12.2.4
In between Richness and Rigor
223
12.2.5
In between Anarchy and Control
225
12.3
Here Be Dragons
225
Epilogue
227
The Interest in Between
227
Social Complexity
228
The Faraway Nearby
230
Appendixes
A An Open Agenda For Complex Adaptive Social Systems
231
A.I Whither Complexity
231
A.2 What Does it Take for a System to Exhibit Complex
Behavior?
233
A.3 Is There an Objective Basis for Recognizing Emergence and
Complexity?
233
A.4 Is There a Mathematics of Complex Adaptive Social Systems?
234
A.5 What Mechanisms Exist for Tuning the Performance of
Complex Systems?
235
A.6 Do Productive Complex Systems Have Unusual Properties?
235
A.7 Do Social Systems Become More Complex over Time
236
A.8 What Makes a System Robust?
236
A.9 Causality in Complex Systems?
237
A.
10
When Does Coevolution Work?
237
A.
11
When Does Updating Matter?
238
A.
12
When Does Heterogeneity Matter?
238
Contents · xi
A.13
How Sophisticated Must Agents Be Before They Are
Interesting?
239
A.
14
What Are the Equivalence Classes of Adaptive Behavior?
240
A.
15
When Does Adaptation Lead to Optimization and
Equilibrium?
241
A.16 How Important Is Communication to Complex Adaptive
Social Systems?
242
A.17 How Do Decentralized Markets Equilibrate?
243
A.I
8
When Do Organizations Arise?
243
A.19 What Are the Origins of Social Life?
244
В
Practices for Computational Modeling
245
B.I Keep the Model Simple
246
B.2 Focus on the Science, Not the Computer
246
B.3 The Old Computer Test
247
B.4 Avoid Black Boxes
247
B.5 Nest Your Models
248
B.6 Have Tunable Dials
248
B.7 Construct Flexible Frameworks
249
B.8 Create Multiple Implementations
249
B.9 Check the Parameters
250
B.10 Document Code
250
B.ll Know the Source of Random Numbers
251
B.12 Beware of Debugging Bias
251
B.13 Write Good Code
251
B.I
4
Avoid False Precision
252
B.15 Distribute Your Code
253
B.
16
Keep a Lab Notebook
253
B.17 Prove Your Results
253
B.I
8
Reward the Right Things
254
Bibliography
255
Index
261 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Miller, John H. Page, Scott E. |
| author_facet | Miller, John H. Page, Scott E. |
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| author_sort | Miller, John H. |
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| discipline | Informatik Soziologie Politologie Psychologie |
| discipline_str_mv | Informatik Soziologie Politologie Psychologie |
| format | Book |
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| genre | (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV022382958 |
| illustrated | Illustrated |
| index_date | 2024-07-02T17:12:00Z |
| indexdate | 2024-07-09T20:56:26Z |
| institution | BVB |
| isbn | 9780691127026 0691127026 0691130965 9780691130965 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015591919 |
| oclc_num | 122412139 |
| open_access_boolean | |
| owner | DE-12 DE-703 DE-N2 DE-19 DE-BY-UBM DE-91 DE-BY-TUM DE-384 DE-M347 DE-188 DE-473 DE-BY-UBG DE-M382 |
| owner_facet | DE-12 DE-703 DE-N2 DE-19 DE-BY-UBM DE-91 DE-BY-TUM DE-384 DE-M347 DE-188 DE-473 DE-BY-UBG DE-M382 |
| physical | XIX, 263 S. Ill., graph. Darst. |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Princeton Univ. Press |
| record_format | marc |
| series2 | Princeton studies in complexity |
| spelling | Miller, John H. Verfasser aut Complex adaptive systems an introduction to computational models of social life John H. Miller and Scott E. Page Princeton, NJ [u.a.] Princeton Univ. Press 2007 XIX, 263 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Princeton studies in complexity Ciências sociais (modelos matemáticos) larpcal Computermodellen Computermodellen gtt Modelli matematici - applicazioni sbt Sciences sociales - Modèles mathématiques Scienze sociali - modelli matematici sbt Sociale relaties Sociale relaties gtt Systèmes sociaux - Modèles mathématiques Mathematisches Modell Sozialwissenschaften Social sciences Mathematical models Social systems Mathematical models Soziales System (DE-588)4055764-9 gnd rswk-swf Soziologische Theorie (DE-588)4077628-1 gnd rswk-swf Computersimulation (DE-588)4148259-1 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Soziales System (DE-588)4055764-9 s Computersimulation (DE-588)4148259-1 s DE-604 Soziologische Theorie (DE-588)4077628-1 s DE-188 Page, Scott E. Verfasser aut Digitalisierung UB Bamberg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015591919&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Miller, John H. Page, Scott E. Complex adaptive systems an introduction to computational models of social life Ciências sociais (modelos matemáticos) larpcal Computermodellen Computermodellen gtt Modelli matematici - applicazioni sbt Sciences sociales - Modèles mathématiques Scienze sociali - modelli matematici sbt Sociale relaties Sociale relaties gtt Systèmes sociaux - Modèles mathématiques Mathematisches Modell Sozialwissenschaften Social sciences Mathematical models Social systems Mathematical models Soziales System (DE-588)4055764-9 gnd Soziologische Theorie (DE-588)4077628-1 gnd Computersimulation (DE-588)4148259-1 gnd |
| subject_GND | (DE-588)4055764-9 (DE-588)4077628-1 (DE-588)4148259-1 (DE-588)4143413-4 |
| title | Complex adaptive systems an introduction to computational models of social life |
| title_auth | Complex adaptive systems an introduction to computational models of social life |
| title_exact_search | Complex adaptive systems an introduction to computational models of social life |
| title_exact_search_txtP | Complex adaptive systems an introduction to computational models of social life |
| title_full | Complex adaptive systems an introduction to computational models of social life John H. Miller and Scott E. Page |
| title_fullStr | Complex adaptive systems an introduction to computational models of social life John H. Miller and Scott E. Page |
| title_full_unstemmed | Complex adaptive systems an introduction to computational models of social life John H. Miller and Scott E. Page |
| title_short | Complex adaptive systems |
| title_sort | complex adaptive systems an introduction to computational models of social life |
| title_sub | an introduction to computational models of social life |
| topic | Ciências sociais (modelos matemáticos) larpcal Computermodellen Computermodellen gtt Modelli matematici - applicazioni sbt Sciences sociales - Modèles mathématiques Scienze sociali - modelli matematici sbt Sociale relaties Sociale relaties gtt Systèmes sociaux - Modèles mathématiques Mathematisches Modell Sozialwissenschaften Social sciences Mathematical models Social systems Mathematical models Soziales System (DE-588)4055764-9 gnd Soziologische Theorie (DE-588)4077628-1 gnd Computersimulation (DE-588)4148259-1 gnd |
| topic_facet | Ciências sociais (modelos matemáticos) Computermodellen Modelli matematici - applicazioni Sciences sociales - Modèles mathématiques Scienze sociali - modelli matematici Sociale relaties Systèmes sociaux - Modèles mathématiques Mathematisches Modell Sozialwissenschaften Social sciences Mathematical models Social systems Mathematical models Soziales System Soziologische Theorie Computersimulation Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015591919&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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