Variational Free Energy and Economics Optimizing With Biases and Bounded Rationality.

Morten Henriksen

doi:10.3389/fpsyg.2020.549187

Abstract

The purpose of this paper is to offer a new framework for understanding action, optimization, and choice when applied to economic theory more generally. By drawing upon the concept known as the variational free energy principle, the paper will explore how this principle can be used to temper rational choice theory by re-formulating how agents optimize. The approach will result in agent behavior that encompasses a wide range of so-called cognitive biases, as seen in the scientific literature of behavioral economics, but instead of using these biases as further indications of market inefficiencies or market failures, the paper will likewise attempt to show the limits to which these biases can inform or critique standard economic theory. The paper therefore offers up a “middle of the road” approach, in which the neoclassical agent is not quite as “rational” as rational choice theory assumes, but at the same time, not quite as irrational as behavioral economics would often have us believe.

Highlights

In the theory of optimal control learning, the goal is to select an action that maximizes some value function such that the preferred state of the world would manifest given an action
In Bellman’s optimality principle, problems and objectives are more or less the same, meaning that problems are framed in terms of reaching an objective or a goal
Economics provides an axiomatic explanation to human action and presumes a set of behavioral laws on the basis of mathematical necessity/design

Summary

INTRODUCTION

In the theory of optimal control learning, the goal is to select an action that maximizes some value function such that the preferred state of the world would manifest given an action. Change during the discounting period in response to information gain with a far higher probability, reflecting belief updating and a preceding search function (order) indicating the appropriateness of a given policy (uncertainty resolution) (Kurth-Nelson et al, 2012) This approach will hereby differ from models that explain temporal discounting in terms of temporal projection or future episodic thinking (Johnson and Redish, 2007; Kurth-Nelson et al, 2012; van der Meer et al, 2012) and will be more in line with suggestions from construal level theory (Trope and Liberman, 2010), where the goal is to figure out how to traverse a distance under various levels of abstraction, or as the free energy approach would put it, various degrees of uncertainty about state transitions (Schultz, 2016; Coddington and Dudman, 2017; Covey and Cheer, 2019). If an agent is indifferent between two outcomes, the agent is not resolving uncertainty and is not acting

CONCLUSION

DATA AVAILABILITY STATEMENT