Collapse Pressure: Microfoundations, Macroeconomic Fragility, and Decision Agents (Three Papers)

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Authors: Larry Lim Kheng Cheong
Cited by: 0

Abstract

This record contains three closely related papers introducing Collapse Pressure as a unifying mechanism for decision-making under irreversibility. The first paper develops Collapse Pressure as a latent pre-choice state in individual decision-making, formalizing hesitation, memory, and delayed action as a hysteretic process rather than instantaneous optimization. Decisions occur when accumulated internal pressure exceeds a threshold, producing sudden “snap” choices without invoking irrationality. The second paper extends this mechanism to the macroeconomic level, showing how aggregate Collapse Pressure can emerge endogenously across agents during prolonged periods of stability. When many agents approach their action thresholds simultaneously, small shocks can trigger correlated collapses, liquidity breakdowns, and systemic fragility. The third paper applies Collapse Pressure to artificial intelligence, proposing a class of collapse-based decision agents designed for non-stationary and irreversible environments. These agents delay action until internal thresholds are crossed, improving robustness under regime shifts compared to continuous optimization or standard reinforcement learning. Together, these three papers establish Collapse Pressure as a general framework spanning microeconomics, macroeconomic fragility, and artificial decision systems.This Zenodo record serves as a time-stamped conceptual foundation. Forthcoming books — Almost Successful, Fragile by Design, and Before the Choice — will cite this record as supplementary theoretical groundwork and extend the ideas to broader economic and institutional contexts.

Fields of Study & Subjects

Decision-Making and Behavioral Economics Economic Theory and Institutions Complex Systems and Time Series Analysis

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
28 January 2026
Language
EN
Document type
Preprint