Cognitive Energy Cost of Informed Decisions

ArXiv ID: 2310.15082 “View on arXiv”

Authors: Unknown

Abstract

Time irreversibility in neuronal dynamics has recently been demonstrated to correlate with various indicators of cognitive effort in living systems. Using Landauer’s principle, which posits that time-irreversible information processing consumes energy, we establish a thermodynamically consistent measure of cognitive energy cost associated with belief dynamics. We utilize this concept to analyze a two-armed bandit game, a standard decision-making framework under uncertainty, considering exploitation, finite memory, and concurrent allocation to both game options or arms. Through exploitative, prediction-error-based belief dynamics, the decision maker incurs a cognitive energy cost. Initially, we observe the rise of dissipative structures in the steady state of the belief space due to time-reversal symmetry breaking at intermediate exploitative levels. To delve deeper into the belief dynamics, we liken it to the behavior of an active particle subjected to state-dependent noise. This analogy enables us to relate emergent risk aversion to standard thermophoresis, connecting two apparently unrelated concepts. Finally, we numerically compute the time irreversibility of belief dynamics in the steady state, revealing a strong correlation between elevated - yet optimized - cognitive energy cost and optimal decision-making outcomes. This correlation suggests a mechanism for the evolution of living systems towards maximally out-of-equilibrium structures.

Keywords: Thermodynamics, Time Irreversibility, Belief Dynamics, Landauer’s Principle, Active Particles, Decision Theory / Cognitive Science

Complexity vs Empirical Score

• Math Complexity: 8.5/10
• Empirical Rigor: 3.0/10
• Quadrant: Lab Rats
• Why: The paper relies heavily on advanced mathematical concepts from thermodynamics and stochastic processes (Landauer’s principle, time irreversibility, active particle models), but it lacks any backtesting, real-world datasets, or implementation-focused code, focusing instead on theoretical modeling and numerical simulations within a controlled setup.

  flowchart TD
    A["Research Goal:<br/>Quantify Cognitive Energy Cost of Decisions"] --> B["Methodology:<br/>Landauer's Principle &<br/>Two-Armed Bandit Game"]
    B --> C["Input Data:<br/>Exploitative Belief Dynamics<br/>Finite Memory"]
    C --> D["Computational Process:<br/>Numerical Simulation of<br/>Time-Irreversibility & Thermodynamics"]
    D --> E["Key Findings:<br/>1. Time-Irreversibility & Cost Correlation<br/>2. Emergent Risk Aversion (Thermophoresis)<br/>3. Optimization via Maximal Out-of-Equilibrium Structures"]