A Defeasible Calculus for Zetetic Agents

TL;DR

This paper develops a logical calculus for modeling rational inquiry in AI agents, focusing on defeasible inferences related to questions, and extends previous work to include new types of erotetic inferences.

Contribution

It introduces an improved sequent calculus for defeasible erotetic inferences, enabling better modeling of zetetic norms in intelligent inquiry systems.

Findings

The calculus captures erotetic defeat mechanisms.

It supports computational properties for AI zetetic agents.

Extension includes a new class of defeasible erotetic inferences.

Abstract

The study of defeasible reasoning unites epistemologists with those working in AI, in part, because both are interested in epistemic rationality. While it is traditionally thought to govern the formation and (with)holding of beliefs, epistemic rationality may also apply to the interrogative attitudes associated with our core epistemic practice of inquiry, such as wondering, investigating, and curiosity. Since generally intelligent systems should be capable of rational inquiry, AI researchers have a natural interest in the norms that govern interrogative attitudes. Following its recent coinage, we use the term "zetetic" to refer to the properties and norms associated with the capacity to inquire. In this paper, we argue that zetetic norms can be modeled via defeasible inferences to and from questions---a.k.a erotetic inferences---in a manner similar to the way norms of epistemic rationality are represented by defeasible inference rules. We offer a sequent calculus that accommodates the unique features of "erotetic defeat" and that exhibits the computational properties needed to inform the design of zetetic agents. The calculus presented here is an improved version of the one presented in Millson (2019), extended to cover a new class of defeasible erotetic inferences.