# Extending Schelling’s segregation model from self orientation to social orientation

## TL;DR

This paper extends Schelling’s segregation model by incorporating social orientation, showing how agents considering others' well-being can reduce segregation and improve community stability.

## Contribution

The novel contribution is introducing relocation rules based on social orientation to better model human communal behavior in segregation dynamics.

## Key findings

- Socially oriented agents reduce segregation and increase global stability in simulations.
- New relocation rules lower relocation costs and social costs while maintaining satisfaction.
- The model shows how local rational decisions can lead to more integrated and resilient communities.

## Abstract

Schelling’s segregation model demonstrates how simple local rules can generate large-scale social patterns, yet it assumes agents act myopically and ignore the broader consequences of their moves. We extend this framework by introducing social orientation as a behavioral microfoundation, reflecting humans’ communal nature. Socially oriented agents follow boundedly rational heuristics that account for the satisfaction of prospective neighbors within a two-step horizon of observability, in addition to their own. We formalize this through three relocation rules—negative externality avoiding (NEA), positive externality favoring (PEF), and positive externality optimizing (PEO)—each capturing a different balance between minimizing disruption and promoting stability. Agent-based simulations reveal that these rules, while maintaining satisfaction, consistently reduce segregation, accelerate the attainment of global stability, and lower relocation moves per agent, thereby reducing social costs. These results provide a stronger behavioral foundation for segregation modeling and show how locally rational, socially sensitive decision-making can scale into equilibria that are not just welfare-enhancing but also yield more integrated and resilient communities.