Hierarchical Resource Rationality Explains Human Reading Behavior

2026-03-06

AI Summary

Existing theories struggle to provide a unified account of the coordination between eye movement control and text comprehension during reading. This work proposes the first hierarchical resource-rational framework that integrates multi-scale processes—ranging from word-level eye movements and lexical identification to sentence integration and discourse-level understanding—within a single computational architecture constrained by cognitive and temporal costs. By combining resource-rational optimization, hierarchical decision modeling, and cognitive simulation, the model successfully reproduces a wide spectrum of human reading phenomena, from lexical effects to holistic comprehension. It further reveals an adaptive coordination mechanism among perception, memory, and action under limited cognitive resources, offering a unified and computationally explicit theoretical explanation of reading cognition.

Technology Category

• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Planning, Routing, and Scheduling: Model-Based Reasoning
• Natural Language Processing: Sentence-level Semantics, Textual Inference, etc.

Application Category

• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Web Mining and Content Analysis: Models for Web evolution
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

Reading is a pervasive and cognitively demanding activity that underpins modern human culture. It is a prime instance of a class of tasks where eye movements are coordinated for the purpose of comprehension. Existing theories explain either eye movements or comprehension during reading, but the critical link between the two remains unclear. Here, we propose resource-rational optimization as a unifying principle governing adaptive reading behavior. Eye movements are selected to maximize expected comprehension while minimizing cognitive and temporal costs, organized hierarchically across nested time scales: fixation decisions support word recognition; sentence-level integration guides skipping and regression; and text-level comprehension goals shape memory construction and rereading. A computational implementation successfully replicates an unprecedented range of findings in human reading, from lexical effects to comprehension outcomes. Together, these results suggest that resource rationality provides a general mechanism for coordinating perception, memory, and action in knowledge-intensive human behaviors, offering a principled account of how complex cognitive skills adapt to limited resources.

Problem

• reading behavior
• eye movements
• comprehension
• resource rationality
• cognitive coordination

Innovation

• resource rationality
• hierarchical optimization
• eye movement control
• reading comprehension
• computational modeling