Advances in social simulation : looking in the mirror

Advances in social simulation : looking in the mirror / Harko Verhagen, Melania Borit, Giangiacomo Bravo, Nanda Wijermans, editors.

This book presents the state-of-the-art in social simulation as presented at the Social Simulation Conference 2018 in Stockholm, Sweden. It covers the developments in applications and methods of social simulation, addressing societal issues such as socio-ecological systems and policy making. Methodo...

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Bibliographic Details
Other Authors: Verhagen, Harko, Borit, Melania, Bravo, Giangiacomo, Wijermans, Nanda
Format: eBook
Language:English
Published: Cham : Springer, 2020.
Series:Springer proceedings in complexity.
Subjects:
Sociology > Simulation methods.
Society & social sciences.
Artificial intelligence.
Operational research.
Computer modelling & simulation.
Maths for scientists.
Social Science > General.
Technology & Engineering > Engineering (General)
Business & Economics > Operations Research.
Computers > Computer Simulation.
Mathematics > Applied.
Electronic books.
Online Access:Click for online access
Table of Contents:
  • Intro
  • Preface
  • Organization
  • General Chair
  • Program Committee Chairs
  • Program Committee
  • Additional Reviewers
  • Contents
  • 1 How Social Simulation Could Help Social Science Dealwith Context
  • 1.1 Introduction
  • 1.2 Talking About "Context"
  • 1.2.1 Situational Context
  • 1.2.2 Cognitive Context
  • 1.2.3 Social Context
  • 1.3 How Social Science Deals with Context
  • 1.3.1 Quantitative Social Science
  • 1.3.1.1 Context-Dependency and Randomness
  • 1.3.1.2 Over-generic Cognitive Models
  • 1.3.2 Qualitative Social Science
  • 1.4 Some Ways Agent-Based Social Simulation Could Deal with Context
  • 1.4.1 Implementing Context-Sensitive Agents in Social Simulations
  • 1.4.2 Approaching Context from Qualitative Narratives
  • 1.5 Concluding Discussion
  • References
  • 2 Agent-Based Modeling with and Without Methodological Individualism
  • 2.1 Introduction
  • 2.2 Methodological Individualism
  • 2.3 Agent-Based Modeling
  • 2.4 Are Agent-Based Models Individualistic?
  • 2.5 Should Agent-Based Models Be Individualistic?
  • 2.6 Conclusion
  • References
  • 3 Inflation Expectations in a Small Open Economy
  • 3.1 Introduction
  • 3.2 Results
  • 3.2.1 Stability Under Households Decision
  • 3.3 Concluding Remarks
  • References
  • 4 Qualitative Data in the Service of Model Building: The Case of Structural Shirking
  • 4.1 Introduction
  • 4.2 The Phenomenon Under Investigation: Shirking
  • 4.3 Starting from Theories: Simulation Model of Shirking #1
  • 4.4 Findings of Model #1 and Shortcomings
  • 4.5 Goal of the Study
  • 4.6 Turning to the Empirical World: Developing Model #2
  • 4.6.1 Addressing Gap 1: Legislation Analysis to Define the Concept of Shirking
  • 4.6.2 Addressing Gap 2: Individual In-Depth Interviews to Discover Mechanisms
  • 4.6.3 Supplementing Empirical Findings with Social Scientific Theories
  • 4.6.4 Bringing It All Together: Implementing and Running Model #2
  • 4.7 Discussion
  • References
  • 5 Causation in Agent-Based Computational Social Science
  • 5.1 Introduction
  • 5.2 Why a Causal Theory of Explanation?
  • 5.3 Existing Accounts of Causation in Agent-Based Computational Social Science
  • 5.3.1 Agent Causation
  • 5.3.2 Algorithmic Causation
  • 5.4 Alternative Accounts of Causation
  • 5.4.1 Interventions
  • 5.4.2 Mechanisms
  • 5.5 Conclusion
  • References
  • 6 Times of Crises and Labour Market Reforms
  • 6.1 Introduction and (Short) Model Description
  • 6.2 Results
  • References
  • 7 Selecting the Right Game Concept for Social Simulationof Real-World Systems
  • 7.1 Introduction
  • 7.2 Taxonomy of Game Concepts
  • 7.2.1 List of Game Concepts
  • 7.2.2 Criteria
  • 7.2.3 Selection of Game Concepts
  • 7.3 Discussion
  • 7.4 Future Work
  • Appendix
  • References
  • 8 Physician, Heal Thyself! The Prospects for Using ABM to Target Interventions to Raise ABM Engagement
  • 8.1 Introduction
  • 8.2 A Model Proposal

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