---
title: "Social simulation"
chunk: 1/4
source: "https://en.wikipedia.org/wiki/Social_simulation"
category: "reference"
tags: "science, encyclopedia"
date_saved: "2026-05-05T03:58:43.417449+00:00"
instance: "kb-cron"
---

Social simulation is a research field that applies computational methods to study issues in the social sciences. The issues explored include problems in computational law, psychology, organizational behavior, sociology, political science, economics, anthropology, geography, engineering, archaeology and linguistics (Takahashi, Sallach & Rouchier 2007).
Social simulation aims to cross the gap between the descriptive approach used in the social sciences and the formal approach used in the natural sciences, by moving the focus on the processes/mechanisms/behaviors that build the social reality.
In social simulation, computers support human reasoning activities by executing these mechanisms. This field explores the simulation of societies as complex non-linear systems, which are difficult to study with classical mathematical equation-based models. Robert Axelrod regards social simulation as a third way of doing science, differing from both the deductive and inductive approach; generating data that can be analysed inductively, but coming from a rigorously specified set of rules rather than from direct measurement of the real world. Thus, simulating a phenomenon is akin to generating it—constructing artificial societies. These ambitious aims have encountered several criticisms.
The social simulation approach to the social sciences is promoted and coordinated by four regional associations, the European Social Simulation Association (ESSA) for Europe, the Asian Social Simulation Association (ASSA) for Asia, the Computational Social Science Society of the Americas (CSSS) in North America, and the Pan-Asian Association for Agent-based Approach in Social Systems Sciences (PAAA) in Pacific Asia.

== History and development ==
The history of the agent-based model can be traced back to the Von Neumann machine, a theoretical machine capable of reproducing itself. The device John von Neumann proposed woud follow precisely detailed instructions to fashion a copy of itself. The concept was then improved by von Neumann's friend Stanislaw Ulam, also a mathematician; Ulam suggested that the machine be built on paper, as a collection of cells on a grid. The idea intrigued von Neumann, who drew it up—creating the first of devices later termed cellular automata.
Another improvement was brought by mathematician, John Conway. He constructed the well-known Game of Life. Unlike the von Neumann's machine, Conway's Game of Life operated by simple rules in a virtual world in the form of a 2-dimensional checkerboard.
The birth of the agent-based model as a model for social systems was primarily brought about by a computer scientist, Craig Reynolds. He tried to model the reality of lively biological agents, known as the artificial life, a term coined by Christopher Langton.
Joshua M. Epstein and Robert Axtell developed the first large scale agent model, the Sugarscape, to simulate and explore the role of social phenomena such as seasonal migrations, pollution, sexual reproduction, combat, transmission of disease, and even culture.
Kathleen M. Carley published "Computational Organizational Science and Organizational Engineering" defining the movement of simulation into
organizations, established a journal for social simulation applied to organizations and complex socio-technical systems: Computational and Mathematical Organization Theory, and was the founding president of the North American Association of Computational Social and Organizational Systems that morphed into the current CSSSA.
Nigel Gilbert published with Klaus G. Troitzsch the first textbook on social simulation: "Simulation for the Social Scientist" (1999) and established its most relevant journal: the Journal of Artificial Societies and Social Simulation.
More recently, Ron Sun developed methods for basing agent-based simulation on models of human cognition, known as cognitive social simulation (see (Sun 2006))

== Topics ==
Here are some sample topics that have been explored with social simulation:

Social norms: Robert Axelrod has used simulations to investigate the foundation of morality; others have modeled the emergence of norms using memes, or how social norms and emotions can regulate each other.
Institutions: by investigating under what conditions agents manage to coordinate, or by modeling the works of Robert Putnam on civic traditions
Reputation, for example by making agents with a model of reputation from Pierre Bourdieu (image, social esteem, and prestige) and observing their behavior in a virtual marketplace.
Knowledge transmission and the social process of science: there is a special section on that topic in the Journal of Artificial Societies and Social Simulation
Elections: Kim (2011) has modeled a psychological model of judgement from previous research (notably featuring motivated reasoning), and compared the statistical regularities of the simulation with empirical observations of voter behavior; others have compared delegation methods.
Economics: see computational economics and agent-based computational economics.

== Types of simulation and modeling ==
Social simulation can refer to a general class of strategies for understanding social dynamics using computers to simulate social systems. Social simulation allows for a more systematic way of viewing the possibilities of outcomes.
There are four major types of social simulation: 

System level simulation.
System level modeling.
Agent-based simulation.
Agent-based modeling.
A social simulation may fall within the rubric of computational sociology which is a recently developed branch of sociology that uses computation to analyze social phenomena. The basic premise of computational sociology is to take advantage of computer simulations (Polhill & Edmonds 2007) in the construction of social theories. It involves the understanding of social agents, the interaction among these agents, and the effect of these interactions on the social aggregate.  Although the subject matter and methodologies in social science differ from those in natural science or computer science, several of the approaches used in contemporary social simulation originated from fields such as physics and artificial intelligence.