Bounded Rational Decision-Making in Changing Environments

TL;DR

This paper explores how bounded rational decision-makers handle changing environments by borrowing concepts from non-equilibrium thermodynamics to quantify inefficiencies caused by environmental changes during decision computation.

Contribution

It introduces a thermodynamics-inspired framework to quantify decision-making inefficiencies in dynamic environments, extending bounded rationality models to non-stationary settings.

Findings

Quantifies utility loss due to environmental changes.

Links decision-making inefficiencies to thermodynamic concepts.

Demonstrates the framework with simulations.

Abstract

A perfectly rational decision-maker chooses the best action with the highest utility gain from a set of possible actions. The optimality principles that describe such decision processes do not take into account the computational costs of finding the optimal action. Bounded rational decision-making addresses this problem by specifically trading off information-processing costs and expected utility. Interestingly, a similar trade-off between energy and entropy arises when describing changes in thermodynamic systems. This similarity has been recently used to describe bounded rational agents. Crucially, this framework assumes that the environment does not change while the decision-maker is computing the optimal policy. When this requirement is not fulfilled, the decision-maker will suffer inefficiencies in utility, that arise because the current policy is optimal for an environment in the past. Here we borrow concepts from non-equilibrium thermodynamics to quantify these inefficiencies and illustrate with simulations its relationship with computational resources.