Advances in social simulation looking in the mirror /: looking in the mirror. (2020)

• Record Type: Book
• Further Information: Note: Harko Verhagen, Melania Borit, Giangiacomo Bravo, Nanda Wijermans, editors.
• Other Names: Verhagen, Harko; Borit, Melania; Bravo, Giangiacomo; Wijermans, Nanda
• 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
• Publisher Details: Cham : Springer
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 301.01/1; Sociology -- Simulation methods; Electronic books; Electronic books
• Languages: English
• ISBNs: 9783030341275; 3030341275
• Related ISBNs: 3030341267; 9783030341268
• Notes: Note: Includes bibliographical references and index.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.