TAPO-Description Logic for Information Behavior: Refined OBoxes, Inference, and Categorical Semantics

TL;DR

This paper introduces a layered TAPO-description logic framework with categorical semantics to analyze complex information behavior, including static knowledge, procedural actions, and external influences.

Contribution

It refines TAPO-description logic into a layered formalism with explicit semantics and inference, enabling comprehensive modeling of information-seeking behaviors.

Findings

Developed a layered formalism with static, procedural, and oracle-sensitive layers.

Formulated a core inference system covering reasoning, procedural transitions, and external imports.

Illustrated the framework with examples of search and review-sensitive behaviors.

Abstract

This paper develops a refined version of TAPO-description logic for the analysis of information behavior. The framework is treated not as a single homogeneous object logic, but as a layered formalism consisting of a static descriptive layer (TBox/ABox), a procedural layer (PBox), and an oracle-sensitive layer (OBox). To make this architecture mathematically explicit, we introduce a metalevel guard-judgment layer governing procedural branching and iteration. On this basis we formulate a core inference system for TAPO-description logic, covering static TBox/ABox reasoning, guarded procedural transition in the PBox, and validated external import in the OBox. We then give a categorical semantics for the resulting framework and indicate its sheaf-theoretic refinement. The theory is illustrated by examples of information-seeking behavior, including simple search behavior and review-sensitive ordering behavior in a curry restaurant. The aim is to treat not only static knowledge representation but also hesitation, external consultation, and action-guiding update within a unified logical setting.