Abstract

The study of ecological rationality investigates an alternative to the view that rational decisions under environmental uncertainty are optimal probabilistic decisions. Focusing on the ecological rationality of simple heuristics, critics, in contrast, have enlisted Marr’s levels of analysis and the distinction between function and mechanism to argue that the study of ecological rationality addresses the question of how organisms make decisions, but not the question of what constitutes a rational decision and why. The claim is that the insights of ecological rationality are, after the fact, reducible to instances of optimal Bayesian inference and require principles of Bayesian rationality to explain. This chapter responds to these critiques by clarifying that ecological rationality is more than a set of algorithmic conjectures. It is also founded on statistical commitments governing the treatment of unquantifiable uncertainty. This statistical perspective establishes why ecological rationality is distinct from Bayesian optimality, is incompatible with Marr’s levels of analysis, and undermines a strict separation of function and mechanism. This argument finds support in Marr’s broader but largely overlooked views on information processing systems and Savage’s stance on the limits on Bayesian decision theory. All rationality principles make assumptions, and the defining characteristic of ecological rationality is the assumption that the uncertainty of the natural world will often make optimal probabilistic responses indeterminable.