Attention! Dynamic Epistemic Logic Models of (In)attentive Agents

TL;DR

This paper extends dynamic epistemic logic models to better represent selective attention and inattentional blindness, allowing agents to focus on subsets of information and default beliefs about unattended facts, with efficient event model representations.

Contribution

It introduces a generalized logic for propositional attention, models inattentional blindness with default beliefs, and provides a linear representation of event models using a new logical language.

Findings

The logic is sound and complete.

Event models can be represented linearly in size.

The framework captures inattentional blindness phenomena.

Abstract

Attention is the crucial cognitive ability that limits and selects what information we observe. Previous work by Bolander et al. (2016) proposes a model of attention based on dynamic epistemic logic (DEL) where agents are either fully attentive or not attentive at all. While introducing the realistic feature that inattentive agents believe nothing happens, the model does not represent the most essential aspect of attention: its selectivity. Here, we propose a generalization that allows for paying attention to subsets of atomic formulas. We introduce the corresponding logic for propositional attention, and show its axiomatization to be sound and complete. We then extend the framework to account for inattentive agents that, instead of assuming nothing happens, may default to a specific truth-value of what they failed to attend to (a sort of prior concerning the unattended atoms). This feature allows for a more cognitively plausible representation of the inattentional blindness phenomenon, where agents end up with false beliefs due to their failure to attend to conspicuous but unexpected events. Both versions of the model define attention-based learning through appropriate DEL event models based on a few and clear edge principles. While the size of such event models grow exponentially both with the number of agents and the number of atoms, we introduce a new logical language for describing event models syntactically and show that using this language our event models can be represented linearly in the number of agents and atoms. Furthermore, representing our event models using this language is achieved by a straightforward formalisation of the aforementioned edge principles.