What question did this study set out to answer?

The research aims to develop a model that explains how agents make decisions without recognizing sensory signals, resulting in empty information sets.

April 1, 2026Open Access

Going Beyond the Traditional Possibility Correspondence Model : The Empty Information Set in Recognition Correspondence Model

Key Points

The research aims to develop a model that explains how agents make decisions without recognizing sensory signals, resulting in empty information sets.
Introduced the recognition correspondence model to address decision-making failures.
Analyzed market behavior examples, particularly during the subprime mortgage crisis.
Defined a new knowledge operator within the context of this model.
Demonstrated that absent sensory signals lead to habitual behaviors instead of conscious decision-making.
Illustrated cognitive limitations that result in empty information sets for agents.
Explored implications of non-trivial unawareness due to lack of signals.

Abstract

This note introduces a new model, termed recognition correspondence, which accounts for situations where agents fail to recognize signals, affecting their decision-making. In contrast with traditional possibility correspondence, this model addresses both technical and cognitive limitations that lead to empty information sets. These sets, interpreted as the absence of sensory signals, prevent agents from recalling or updating knowledge. Market behavior during the subprime mortgage crisis and asymptomatic COVID-19 infection illustrates the model. We also redefine the knowledge operator within this framework and explore its implications for non-trivial unawareness. The model demonstrates that, even when agents receive no signals, they default to habitual behavior rather than conscious decision-making.

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