RAINO Framework Brings Structure to Realism in Agent-Based Models
A systematic review finds realism in ABM is poorly theorized—RAINO offers a solution.
Deep Dive
Researchers Vanhée and Borit present RAINO (Reality Anchor, Input, Output), a conceptual framework for operationalizing realism in agent-based modelling. Their systematic literature review reveals that realism is rarely defined consistently, and methods for achieving it lack justification. RAINO identifies Reality Anchors—such as empirical data, formal theory, expert knowledge, and common-sense expectations—applied either as model input or output. Accepted at Social Simulation Conference 2025.
Key Points
- Systematic review of 100+ ABM papers reveals widespread lack of consistent realism definitions.
- RAINO framework identifies 4 Reality Anchors: empirical data, formal theory, expert knowledge, common-sense expectations.
- Accepted at Social Simulation Conference 2025; available on arXiv (2606.05167).
Why It Matters
A structured framework for realism helps ABM researchers build more trustworthy simulations and communicate limitations clearly.