Finite Cognition and Model Selection: An Empirical Test of Agent-Relative Constraints in Scientific Choice

This paper proposes an empirical framework to test the hypothesis that model selection is constrained not only by empirical adequacy and formal complexity, but also by the cognitive limitations of agents. We formalize a selection functional incorporating empirical error, cognitive cost, and error severity, and derive experimentally testable predictions that diverge from standard Bayesian and Minimum Description Length (MDL) approaches. A controlled experimental protocol is outlined to evaluate whether human agents systematically deviate from purely formal optimization due to finite cognitive constraints.