# Inferring Causality in Agent-Based Simulations - Literature Review

## TL;DR

This literature review examines various methods for inferring causality in agent-based simulations to better understand emergent behaviors and system structures across complex systems.

## Contribution

It provides a comparative analysis of existing approaches for identifying causal relationships in agent-based models, highlighting their strengths and limitations.

## Key findings

- Different causal inference methods vary in accuracy and applicability.
- Some approaches effectively uncover causal links in complex agent interactions.
- The review identifies gaps and future directions in causal analysis for agent-based systems.

## Abstract

Complex systems have interested researchers across a broad range of fields for many years and as computing has become more accesible and feasible, it is now possible to simulate aspects of these systems. A major point of research is how emergent behaviour arises and the underlying causes of it. This paper aims to discuss and compare different methods of identifying causal links between agents in such systems in order to gain further understanding of the structure.