Computational Experiments

About the Author xv
Preface xvii

1 Origin and Goal of Computational Experiments 1
1.1 Complexity Science 1
1.2 Methodological Framework of Computational Experiments 16
1.3 Organizational Structure of the Book 25
1.4 Chapter Summary 31

2 Computational Experiments for Physical Systems 37
2.1 The Principle of Similarity and System Modeling 37
2.2 Simulation Examples and Concepts 46
2.3 Experimental Theory 58
2.4 Statistical Methods 66
2.5 Chapter Summary 72

3 Computational Experiments for Social Systems 75
3.1 Social Simulation Method 75
3.2 Simulation of Social Systems 91
3.3 Causal Inference 104
3.4 A Classic Case of Social Simulation 111
3.5 Chapter Summary 126

4 Methodological Framework of Computational Experiments 133
4.1 Framework of Computational Experiment Method 133
4.2 Computational Experiment Platform Architecture 141
4.3 Operation Steps of the Experimental Platform 151
4.4 Chapter Summary 168

5 The First Step - Building an Artificial Society 171
5.1 Analysis of Characteristics of Artificial Society 171
5.2 The Modeling Framework of Artificial Society 177
5.3 The Modeling Framework of Artificial Society 184
5.4 Case Study: Intelligent Logistics System 190
5.5 Chapter Summary 199

6 The Second Step - Constructing the Experimental System 203
6.1 From Game Worlds to Virtual Societies 203
6.2 Virtual Experiments with Humans Outside the Loop 211
6.3 Model Integration of Social Simulators 214
6.4 Case Study 224
6.5 Chapter Summary 232

7 The Third Step-Experimental Design and Generative Explanation 235
7.1 Comprehensive Framework of Computational Experiment Design 236
7.2 Introduction to Experimental Design Methods 243
7.3 Design of Scenario Generation Algorithm 255
7.4 Case Study: API Service Market 265
7.5 Chapter Summary 273

8 The Fourth Step - Experimental Analysis and Causal Inference 279
8.1 The Laws of System Complexity 279
8.2 Causal Inference Framework of Computational Experiments 287
8.3 Causal Inference Layers in Computational Experiments 298
8.4 Case Study: Algorithmic Behavior on Internet Platforms 307
8.5 Chapter Summary 317

9 The Fifth Step - Maturity Evaluation of Computational Experiments 321
9.1 Theoretical Foundation of Computational Experiment Validation 322
9.2 Model Evaluation Framework in Computational Epidemiology 332
9.3 Capability Maturity of Computational Epidemiological Models 337
9.4 Case Study of Computational Epidemiological Models 347
9.5 Chapter Summary 356

10 LLM-Based Agents and Social Simulation 361
10.1 The Architecture of LLM-Based Agent 362
10.2 Stanford Smallville 371
10.3 LLM-Based Agent's Capability Pool 380
10.4 Applications of LLM-Based Agent Simulation 390
10.5 Chapter Summary 401

11 Large Language Model Agents and Workflow 407
11.1 Collaboration Framework of AI Agents 408
11.2 The Orchestration Methods of Multiagents 420
11.3 Automation of Computational Experiments 430
11.4 The Challenges of Multiagent Collaboration 438
11.5 Chapter Summary 447

12 Roadmap of Computational Experiment Method 451
12.1 Roadmap of Computational Experiment Method 451
12.2 Q1: How to Conduct Computational Modeling of the Real World 454
12.3 Q2: How to Conduct Causal Reasoning in a Virtual World 456
12.4 Q3: How to Ensure That Experimental Laws Hold in Reality? 461
12.5 Traditional Simulation vs. Generative Simulation 463
12.6 Chapter Summary 468

References 468
A Appendix 471
Index 511