An axiomatic formalization of bounded rationality based on a utility-information equivalence

TL;DR

This paper introduces an axiomatic framework for bounded rational decision-making that incorporates resource costs, linking utility and information through a variational principle, and generalizing the classic maximum expected utility approach.

Contribution

It presents a novel axiomatic formalization of bounded rationality that integrates resource costs and establishes a utility-information equivalence based on a variational principle.

Findings

Derives a unique utility-probability conversion law

Shows how to optimize decision-making with resource constraints

Recovers the classic MEU principle when resource costs are ignored

Abstract

Classic decision-theory is based on the maximum expected utility (MEU) principle, but crucially ignores the resource costs incurred when determining optimal decisions. Here we propose an axiomatic framework for bounded decision-making that considers resource costs. Agents are formalized as probability measures over input-output streams. We postulate that any such probability measure can be assigned a corresponding conjugate utility function based on three axioms: utilities should be real-valued, additive and monotonic mappings of probabilities. We show that these axioms enforce a unique conversion law between utility and probability (and thereby, information). Moreover, we show that this relation can be characterized as a variational principle: given a utility function, its conjugate probability measure maximizes a free utility functional. Transformations of probability measures can then be formalized as a change in free utility due to the addition of new constraints expressed by a target utility function. Accordingly, one obtains a criterion to choose a probability measure that trades off the maximization of a target utility function and the cost of the deviation from a reference distribution. We show that optimal control, adaptive estimation and adaptive control problems can be solved this way in a resource-efficient way. When resource costs are ignored, the MEU principle is recovered. Our formalization might thus provide a principled approach to bounded rationality that establishes a close link to information theory.