Sponsor
Portland State University. Systems Science Graduate Program
First Advisor
Rajesh Venkatachalapathy
Term of Graduation
Summer 2025
Date of Publication
8-6-2025
Document Type
Thesis
Degree Name
Master of Science (M.S.) in Systems Science
Department
Systems Science
Language
English
Subjects
Complex Systems, Computational Social Science, Evolutionary Economics, Evolutionary Game Theory
Physical Description
1 online resource (xi, 70 pages)
Abstract
In their 2000 paper, The Emergence of Classes in a Multi-Agent Bargaining Model, Axtell, Epstein, and Young introduced an agent-based bargaining model to study how social norms can emerge and persist from the decentralized, asynchronous interactions of individual agents in the presence of noise, even when these agents have no predefined preferences or advantages. This thesis extends their model by incorporating structured interaction networks, allowing us to investigate how the topology of agent interactions influences long-run dynamics and norm formation. Using a custom simulation package built in the Julia programming language, we replicate the original results under a complete interaction graph and then conduct a comparative analysis using four random graph models: Erdős-Rényi, Small-World, Scale-Free, and Stochastic Block Models. We analyze noise-induced transitions from the metastable, discriminatory "fractious" state to the stochastically stable "equity" norm, highlighting how structural features such as degree heterogeneity, clustering, and community structure shape both the inertia, i.e., waiting time until transition, and the dynamical path of normative convergence. Our findings emphasize that differences in network topology affect the speed, variability, and trajectory of population-level transitions. To ensure meaningful comparison across models, we use a systematic approach to parameterization and introduce a revised stopping condition, the partially-reinforced equity condition, which more accurately captures system inertia and enables simulations at larger population scales. This thesis contributes both methodological tools and theoretical insights to the study of evolutionary game theory, social learning, and complex adaptive systems.
Rights
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Persistent Identifier
https://archives.pdx.edu/ds/psu/44220
Recommended Citation
Foresman, Parker, "Emergence of Norms in the Presence of Social Network Structure in a Stochastic Evolutionary Game Theory Model" (2025). Dissertations and Theses. Paper 6968.