# Models we Can Trust: Toward a Systematic Discipline of (Agent-Based) Model Interpretation and Validation

arXiv: https://arxiv.org/abs/2102.11615 · HTML: https://mlsanity.com/paper/2102.11615/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 117 references that are in the map.
- First posted on arXiv 23 Feb 2021.

## Builds on (most cited first, 3 of 3)

- [Majority Opinion Diffusion in Social Networks: An Adversarial Approach](https://mlsanity.com/paper/2012.03143/) (2020)
- [Nash Equilibrium and Bisimulation Invariance](https://mlsanity.com/paper/1808.09213/) (2018)
- [Stochastic Stability in Schelling's Segregation Model with Markovian Asynchronous Update](https://mlsanity.com/paper/1807.05419/) (2018)

## Built on by (most cited first, 1 of 1)

- [Simulation-Based Counterfactual Causal Discovery on Real World Driver Behaviour](https://mlsanity.com/paper/2306.03354/) (2023)

## Abstract (arXiv)

We advocate the development of a discipline of interacting with and extracting information from models, both mathematical (e.g. game-theoretic ones) and computational (e.g. agent-based models). We outline some directions for the development of a such a discipline: - the development of logical frameworks for the systematic formal specification of stylized facts and social mechanisms in (mathematical and computational) social science. Such frameworks would bring to attention new issues, such as phase transitions, i.e. dramatical changes in the validity of the stylized facts beyond some critical values in parameter space. We argue that such statements are useful for those logical frameworks describing properties of ABM. - the adaptation of tools from the theory of reactive systems (such as bisimulation) to obtain practically relevant notions of two systems "having the same behavior". - the systematic development of an adversarial theory of model perturbations, that investigates the robustness of conclusions derived from models of social behavior to variations in several features of the social dynamics. These may include: activation order, the underlying social network, individual agent behavior.