# Escape dynamics based on bounded rationality

## TL;DR

This paper models escape dynamics considering bounded rationality, revealing that such strategies can improve efficiency and lead to meta-stable states, with escape times scaling power-law with system size.

## Contribution

It introduces a cellular automaton model incorporating bounded rational behavior via heterogeneous information, advancing understanding of evacuation dynamics.

## Key findings

- Bounded rational strategies improve escape efficiency.
- A meta-stable state emerges during evacuation.
- Escape time scales as a power-law with system size.

## Abstract

The bounded rationality plays a vital role in the collective behavior of the evacuation process. Also investigating human behavior in such an extreme situation is a continuing concern within social psychology. In this paper, we construct a cellular automaton (CA) model for the escape dynamics, and the bounded rational behavior induced by heterogeneous information is introduced. The non-trivial behavior shows in the replicator dynamics method with mean field approximation, where people's perception of the distribution of population and velocity is reduced to an average value in a certain direction. Analyzing the escape efficiency shows that under the premise of rationality, the bounded rational strategy can get higher performance. Interestingly, a quantifiable meta-stable state appears in the escape process, and the escape time is power-law dependent on system size.