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Intensional Inheritance Between Concepts: An Information-Theoretic Interpretation

Ben Goertzel

TL;DR

The paper addresses formalizing intensional inheritance between concepts $F$ and $W$ through information-theoretic measures. It develops both Shannon and algorithmic information theory formulations, incorporating interaction information among properties to quantify $I(F;W)$ and the conditional $P(W|F)$. A tractable special case with mutually exclusive properties yields simple expressions and demonstrates how extensional inheritance arises as a special case when properties are singleton. The framework provides a quantitative tool for reasoning about concept hierarchies in AI systems, linking intensional and extensional inheritance under a unified information-theoretic view.

Abstract

This paper addresses the problem of formalizing and quantifying the concept of "intensional inheritance" between two concepts. We begin by conceiving the intensional inheritance of $W$ from $F$ as the amount of information the proposition "x is $F$ " provides about the proposition "x is $W$. To flesh this out, we consider concepts $F$ and $W$ defined by sets of properties $\left\{F_{1}, F_{2}, \ldots, F_{n}\right\}$ and $\left\{W_{1}, W_{2}, \ldots, W_{m}\right\}$ with associated degrees $\left\{d_{1}, d_{2}, \ldots, d_{n}\right\}$ and $\left\{e_{1}, e_{2}, \ldots, e_{m}\right\}$, respectively, where the properties may overlap. We then derive formulas for the intensional inheritance using both Shannon information theory and algorithmic information theory, incorporating interaction information among properties. We examine a special case where all properties are mutually exclusive and calculate the intensional inheritance in this case in both frameworks. We also derive expressions for $P(W \mid F)$ based on the mutual information formula. Finally we consider the relationship between intensional inheritance and conventional set-theoretic "extensional" inheritance, concluding that in our information-theoretic framework, extensional inheritance emerges as a special case of intensional inheritance.

Intensional Inheritance Between Concepts: An Information-Theoretic Interpretation

TL;DR

The paper addresses formalizing intensional inheritance between concepts and through information-theoretic measures. It develops both Shannon and algorithmic information theory formulations, incorporating interaction information among properties to quantify and the conditional . A tractable special case with mutually exclusive properties yields simple expressions and demonstrates how extensional inheritance arises as a special case when properties are singleton. The framework provides a quantitative tool for reasoning about concept hierarchies in AI systems, linking intensional and extensional inheritance under a unified information-theoretic view.

Abstract

This paper addresses the problem of formalizing and quantifying the concept of "intensional inheritance" between two concepts. We begin by conceiving the intensional inheritance of from as the amount of information the proposition "x is " provides about the proposition "x is . To flesh this out, we consider concepts and defined by sets of properties and with associated degrees and , respectively, where the properties may overlap. We then derive formulas for the intensional inheritance using both Shannon information theory and algorithmic information theory, incorporating interaction information among properties. We examine a special case where all properties are mutually exclusive and calculate the intensional inheritance in this case in both frameworks. We also derive expressions for based on the mutual information formula. Finally we consider the relationship between intensional inheritance and conventional set-theoretic "extensional" inheritance, concluding that in our information-theoretic framework, extensional inheritance emerges as a special case of intensional inheritance.

Paper Structure

This paper contains 23 sections, 33 equations.