The Requirement for Cognition, in an Equation

TL;DR

This paper derives a Requirement Equation (RE) for the evolution of cognition, linking environmental factors to the computational needs of the brain, and explains how brain complexity varies with domain complexity.

Contribution

It introduces the Requirement Equation (RE) that predicts the computational demands of brains based on habitat and biology without assuming specific neural mechanisms.

Findings

In simple domains, shortcut computations suffice for decision-making.

In complex domains, brains build Bayesian models constrained by external reality.

The RE links environmental complexity to cognitive evolution.

Abstract

A model of the evolution of cognition is used to derive a Requirement Equation (RE), which defines what computations the fittest possible brain must make, or must choose actions as if it had made those computations. The terms in the RE depend on factors outside an animals brain, which can be modelled without making assumptions about how the brain works, from knowledge of the animals habitat and biology. In simple domains where the choices of actions have small information content, it may not be necessary to build internal models of reality; short cut computations may be just as good at choosing actions. In complex domains such as 3D spatial cognition, which underpins many complex choices of action, the RE implies that brains build Bayesian internal models of the animals surroundings; and that the models are constrained to be true to external reality.