Social science microsimulation: with 20 tables
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | German |
| Veröffentlicht: |
Berlin [u.a.]
Springer
1996
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XII, 471 S. graph. Darst. |
| ISBN: | 3540615725 |
Internformat
MARC
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| 245 | 1 | 0 | |a Social science microsimulation |b with 20 tables |c Klaus G. Troitzsch ... (eds.) |
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 1996 | |
| 300 | |a XII, 471 S. |b graph. Darst. | ||
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Datensatz im Suchindex
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Table of Contents
Preface V
I Social Science Microsimulation /
Microanalytic Simulation Models 1
1 A Comparison of a 4GL and an Object-oriented Approach in Micro
Macro Simulation 3
by Hans-Dieter Heike, Kai Beckmann, Achim Kaufmann, Harald Ritz,
and Thomas Sauerbier
1.1 Introduction. 3
1.2 Darmstadt Micro Macro Simulator. 4
1.3 Fourth Generation Language System . 11
1.4 Application Development Tools. 15
1.5 Object-oriented System. 24
1.6 Concluding Remarks. 30
2 MICSIM: Concept, Developments, and Applications
of a PC Microsimulation Model for Research and Teaching 33
by Joachim Merz
2.1 Microsimulation for Research and Teaching . 33
2.2 Microsimulation — General Characteristics and Requirements 34
2.3 MICSIM - Concept and Substantive Modules. 40
2.4 MICSIM - Realisations and Developments. 50
2.5 MICSIM - Applications. 59
2.6 Concluding Remarks. 62
3 Exploring and Testing Theories: On the Role of Parameter Opti-
mization in Social Science Computer Simulation 66
by Georg Muller
3.1 Simulation Assisted Theory Building. 66
VIH
Table of Contents
3.2 On the Role of Parameter Optimization in Simulation Assisted
Theory Building. 68
3.3 An Example: Exploring and Testing Richardson’s Theory of
Arms Races. 70
3.4 Software Requirements for Parameter Optimization. 74
3.5 Summary and Outlook. 75
4 Why Are We Simulating Anyway? Some Answers from Economics 78
by Edmund Chattoe
4.1 Simulating What?. 78
4.2 Different But Equal Representations of Theory. 82
4.3 Difficulties with Mathematical Representation. 87
4.4 The Possibilities of Simulation. 93
4.5 But Is It Science?. 96
4.6 Conclusion. 102
II Social Science Multilevel Simulation 105
5 Multilevel Simulation 107
by Klaus G. Troitzsch
5.1 Introduction. 107
5.2 Modeling Approaches. 108
5.3 Opinion Formation in a Homogeneous Population . 112
5.4 Attitude Formation in a Homogeneous Population. 113
5.5 Gender Desegregation. 115
5.6 Interactions in Small Groups. 117
5.7 Conclusion. 120
6 Social Science Multilevel Simulation with MIMOSE 123
by Michael Mohring
6.1 Modelling in MIMOSE. 123
6.2 Experimentation with Models. 131
6.3 Conclusions. 136
7 Multilevel Modelling with MIMOSE:
Experience from a Social Science Application 138
by Nicole J. Saam
7.1 The Problem: Military Intervention in Politics. 138
7.2 The Formal Approach to Multilevel Modeling. 139
7.3 The Multilevel Model of Military Intervention in Politics . . . 140
7.4 The Application: Military Intervention in Thailand. 144
7.5 Results. 144
Table of Contents
IX
7.6 Sensitivity Analysis. 148
7.7 Research Questions. 153
8 A Microsimulation Tool for Social Force Models 155
by Péter Molnâr
8.1 Simulation of Pedestrian Traffic. 155
8.2 The Simulation Program. 164
8.3 Summary and Outlook. 168
9 Evolution in Humans of Macro-level Social Stratification and
Language 171
by Allan Mazur
9.1 Introduction. 171
9.2 Modeling Social Stratification. 172
9.3 Modeling Human Language. 174
9.4 Conclusion. 176
10 Survival Analysis, Master Equation, Efficient Simulation of
Path-Related Quantities, and Hidden State Concept of Transitions 179
by Dirk Helbing
10.1 Introduction. 179
10.2 Survival Analysis. 180
10.3 The Master Equation Technique. 184
10.4 Simulation of Path-Related Quantities. 188
10.5 Occurence Probabilities and Occurence Times of Paths . 190
10.6 Effective Cumulative Life-Time Distribution and Hidden State
Concept. 194
10.7 Summary and Outlook. 205
III Game Theory and Cellular Automata 209
11 Game Theory, Decision Making in Conflicts and Computer
Simulations: a Good-Looking Triad 211
by Wim B. G. Liebrand and David M. Messick
11.1 Introduction. 211
11.2 Game Theory . 212
11.3 Decision Making under Uncertainty and Conflict. 214
11.4 Social Dilemmas. 215
11.5 A Model of Decision Making in Social Dilemmas. 216
11.6 The Simulation Environment. 217
11.7 Basic Findings of the Simulations. 219
11.8 Small Groups versus Large Groups. 221
X
Table of Contents
11.9 Cooperation in Large Groups. 223
11.1 OTheoretical Model. 227
11.11 Summary and Conclusions. 233
12 From Life Event Analysis to Life Course Analysis 237
by Ulrich Mueller
12.1 Introduction.237
12.2 From Transition Rate Models to Evolutionary Life History
Analysis. 239
12.3 Stochastic Dynamic Programming in Life Course Analysis:
Basic Concepts and a Simple Model. 249
12.4 Testing the New Models Against Real Data. 260
13 Simulating Cooperation and Competition: Present State and
Future Objectives 264
by Ramzi Suleiman
13.1 Introduction. 264
13.2 Collective Stability in Heterogeneous Populations. 267
13.3 Changing the Strategic Objective . 269
13.4 Introducing Space. 271
13.5 Towards the Simulation of Social Dilemmas. 272
13.6 Towards the Simulation of Intergroup Conflict. 274
13.7 Concluding Remarks. 276
14 Understanding Social Dynamics:
The Cellular Automata Approach 282
by Rainer Hegselmann
14.1 Introduction. 282
14.2 CA and Social Dynamics . 283
14.3 A Short History of CA Based Modeling in the Social Sciences 287
14.4 A Migration Model: Evolution of Support Networks. 291
14.5 Why CA based modeling and simulations?. 302
15 Spatial Evolution of Automata in the Prisoner’s Dilemma 307
by Oliver Kirchkamp
15.1 Introduction. 307
15.2 The Model. 315
15.3 Results with Fixed Learning Rules. 327
15.4 Conclusions. 353
15.5 Proof of Proposition 15.1 355
Table of Contents
XI
16 Simulating the Social Context of Human Choice 359
by Matthew J. Rockloff and Bibb Latane
16.1 Introduction. 359
16.2 Social Impact Theory. 360
16.3 Dynamic Social Impact. 361
16.4 Theory and Data. 364
16.5 Demonstrating Dynamic Social Impact . . . 365
16.6 SITSIM: Predicting the Emergence of Organization. 369
16.7 GroupSim: Tailored to the Task. 370
16.8 Discussion. 374
16.9 Conclusion. 375
IV Distributed Artificial Intelligence 379
17 Simulating Societies using Distributed Artificial Intelligence 381
by Jim Doran
17.1 Introduction. 381
17.2 Modelling Simulation. 381
17.3 Distributed AI. 383
17.4 Agent Designs. 383
17.5 Sets of Intelligent Agents. 386
17.6 Using DAI to Simulate Societies. 386
17.7 Illustrative Examples. 387
17.8 Prospects and Problems. 391
17.9 Acknowledgments. 391
18 Simulating Multi-Agent Interdependencies.
A Two-Way Approach to the Micro-Macro Link 394
by Rosaria Conte and Cristiano Castelfranchi
18.1 Some Requirements for Social Theory. 394
18.2 The Dependence Theory. 399
18.3 The DEPNET Simulator.405
18.4 The Potentialities of DEPNET. 406
18.5 Conclusive Remarks. 412
19 Artificial Intelligence Modelling: Data Driven and
Theory Driven Approaches 416
by Klaus Manhart
19.1 Three Dilemmas of Conventional Computer Models.416
19.2 AI Based Modelling.417
19.3 Theory Driven AI-Modelling . 420
XII
Table of Contents
19.4 Data Driven AI-Modelling.422
19.5 A Mixed Approach: Discovery of Theoretical Explanations for
Group Processes. 424
19.6 Conclusion.429
20 Object-Oriented and Agent-Oriented Simulation:
Implications for Social Science Application 432
by Adelinde Uhrmacher
20.1 Introduction. 433
20.2 Agents: Deliberative, Situated, Reactive, Rational. 434
20.3 The Object-Oriented Simulation System DEVS. . 435
20.4 DEVS and Agent-Oriented Techniques .437
20.5 A Step to Agent-Oriented Simulation — AgedDEVS.438
20.6 Hiring and Firing. 439
20.7 AgedDEVS and Agent-Oriented Simulation. 444
20.8 Conclusions.445
21 Simulation as a Research Strategy 448
by G. Nigel Gilbert
21.1 The Advantages of Simulation. 448
21.2 A Methodology for Simulation Research . 450
21.3 Some Conjectures Arising from the Simulations.452
21.4 Computing Techniques and Tools for Simulation.453
Y Appendix 455
A Environments and Languages to Support Social Simulation 457
Summary of an Informal Discussion by G. Nigel Gilbert
B Computer Simulation and Social Sciences: On the Future of a Dif-
ficult Relation 459
Summary of an Informal Discussion by Klaus G. Troitzsch
Author Index 461
Subject Index
469 |
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| dewey-search | 300/.1/1 20 300.11 |
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| discipline | Soziologie |
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| indexdate | 2025-01-10T13:21:47Z |
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| spelling | Social science microsimulation with 20 tables Klaus G. Troitzsch ... (eds.) Berlin [u.a.] Springer 1996 XII, 471 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Sozialwissenschaften Social sciences -- Simulation methods Sozialwissenschaften (DE-588)4055916-6 gnd rswk-swf Mikrosimulation (DE-588)4131395-1 gnd rswk-swf (DE-588)1071861417 Konferenzschrift 1995 Dagstuhl gnd-content Sozialwissenschaften (DE-588)4055916-6 s Mikrosimulation (DE-588)4131395-1 s DE-604 Troitzsch, Klaus G. 1946- Sonstige (DE-588)143268953 oth Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007324909&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| subject_GND | (DE-588)4055916-6 (DE-588)4131395-1 (DE-588)1071861417 |
| title | Social science microsimulation with 20 tables |
| title_auth | Social science microsimulation with 20 tables |
| title_exact_search | Social science microsimulation with 20 tables |
| title_full | Social science microsimulation with 20 tables Klaus G. Troitzsch ... (eds.) |
| title_fullStr | Social science microsimulation with 20 tables Klaus G. Troitzsch ... (eds.) |
| title_full_unstemmed | Social science microsimulation with 20 tables Klaus G. Troitzsch ... (eds.) |
| title_short | Social science microsimulation |
| title_sort | social science microsimulation with 20 tables |
| title_sub | with 20 tables |
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| topic_facet | Sozialwissenschaften Social sciences -- Simulation methods Mikrosimulation Konferenzschrift 1995 Dagstuhl |
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