The frame problem: Relevance, emotion, and degrees of epistemic success
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Abstract
Abstract: In recent decades, the relationship between Artificial Intelligence and the Epistemology of Emotions has grown in three main ways: through the development of these concepts, their critical evaluation, and the adoption of their findings and perspectives. This paper focuses on the relationship between different theoretical perspectives on emotions and their potential to address a key issue in Artificial Intelligence: the frame problem, which questions the simulation of cognitive processes involved in determining relevance. In addition to the relatively scarce research focussed specifically on this relationship, most existing studies lack clarity in defining which aspect of the frame problem they are addressing. The aim of this paper is to examine the limits and scope of the epistemic function of salience/relevance of emotions in tackling the two main challenges of the efficient aspect of the frame problem. We argue that some epistemological positions are effective in overcoming both the difficulty of regression and the challenges of the vastness of information, while others address only the latter. These divergences show that advances in the epistemological understanding of emotions can have a direct practical application in the advancement of Artificial Intelligence, since they collaborate, through different epistemic degrees, to simulating cognitive processes involved in determining relevance.
Keywords: Frame Problem; Relevance; Salience of Emotions; Degrees of Epistemic Success
Il problema del frame: Rilevanza, emozioni e livelli di successo epistemico
Riassunto: Negli uktimi decenni la relazione tra Intelligenza Artificiale ed Epistemologia delle Emozioni si è intensificata seguendo principalmente tre vie: lo sviluppo di questi concetti, il loro vaglio critico e l’adozione dei loro risultati e prospettive. Il presente articolo si concentra sulla relazione tra l’adozione di differenti prospettive teoriche sulle emozioni e la risoluzione di una questione chiave nell’ambito dell’Intelligenza Artificiale: il problema del frame, che riguarda la simulazione dei processi cognitivi implicati nella determinazione della rilevanza. Oltre alla relativa scarsità di ricerche che si focalizzano in particolare su questa relazione, la maggior parte di questi studi manca di chiarezza nel definire quale degli aspetti del problema del frame venga esplorato. L’obiettivo di questo lavoro è analizzare i limiti e la portata della funzione epistemica della salienza/rilevanza delle emozioni nella risoluzione delle due principali difficoltà dell’aspetto efficiente del problema del frame. Sosteniamo che alcune posizioni epistemologiche coincidono nel superare sia la difficoltà della regressione sia quella della vastità dell’informazione, mentre altre riescono solo nella seconda. Queste divergenze mostrano che vi sono progressi nelle prospettive teoriche epistemologiche delle emozioni che possono avere un utilizzo pratico diretto nello sviluppo dell’Intelligenza Artificiale, poiché esse contribuiscono, con differenti gradi epistemici, alla simulazione dei processi cognitivi implicati nella determinazione della rilevanza.
Parole chiave: Frame Problem; Rilevanza; Salienza delle emozioni; Livelli di successo epistemico
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