A tool for simulated social experiments

Authored by MN Szilagyi, ZC Szilagyi

Date Published: 2000-01

DOI: 10.1177/003754970007400101

Sponsors: American Society for Engineering Education

Platforms: C++

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

A new agent-based model is presented of the investigation of collective behavior with a large number of decision makers operating in a stochastic environment. (An agent is an entity that interacts with and contributes to its environment. A set of agents can be a simplified representation of a society.) The model has three distinctive new features: the number of agents in the model is theoretically unlimited; the agents have various distinct user-defined “personalities;” and the agents are described as combinations of cellular and stochastic learning automata. The combination of different personalities with stochastic learning makes it possible to simulate human-like behavior in social situations when each group member must choose between maximizing selfish interests or collective interests. Our model is a framework to perform various simulated social experiments and assess the propagation of information and human influence in large-scale conflicting environments, e.g., to simulate realistic multi-person social dilemmas. We have developed a computational tool to implement this model. This is a powerful tool for investigating group dynamics that is also an advance in nonlinear dynamic system simulation. It may lead to the discovery of a number of factors influencing human collective behavior.

Tags

Agent-based model Social simulation social dilemma behavioral simulation cellular automaion stochastic learning