Rule Based Models

Rule-based models specify how states or agents change under conditional update rules. They may include deterministic, probabilistic, heuristic, or optimizing behavior.

A rule-based model describes how a state changes when conditions trigger specified actions. The rules may be deterministic or probabilistic, and agents may follow heuristics or optimize within them. The defining feature is an explicit update mechanism that can be traced, not the absence of choice or randomness.

Interactions make a rule set more than a collection of individually sensible instructions. Rule order, simultaneous updates, exceptions, and access to information can change outcomes. Use a small trace to locate the interaction before changing a real procedure. A simulated improvement remains conditional on whether people and systems actually follow the modeled rules.

When to use it

When organizational behavior needs to change through rule redesign; when rule complexity is producing unintended consequences; when the gap between stated and actual rules needs analysis; when understanding how rules create behavioral landscapes.

How it can help

Make triggers, actions, exceptions, and update order explicit. Trace interactions and compare the model with observed practice before changing a procedure.