English

Aggregation and Emergence in Agent-Based Models: A Markov Chain Approach

Adaptation and Self-Organizing Systems 2012-07-11 v1 Statistical Mechanics

Abstract

We analyze the dynamics of agent--based models (ABMs) from a Markovian perspective and derive explicit statements about the possibility of linking a microscopic agent model to the dynamical processes of macroscopic observables that are useful for a precise understanding of the model dynamics. In this way the dynamics of collective variables may be studied, and a description of macro dynamics as emergent properties of micro dynamics, in particular during transient times, is possible.

Keywords

Cite

@article{arxiv.1207.2255,
  title  = {Aggregation and Emergence in Agent-Based Models: A Markov Chain Approach},
  author = {Sven Banisch and Ricardo Lima and Tanya Araújo},
  journal= {arXiv preprint arXiv:1207.2255},
  year   = {2012}
}

Comments

5 pages, 1 figure

R2 v1 2026-06-21T21:33:11.386Z