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AI research explores new computational models for affect and interaction · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Two new research papers explore computational approaches to understanding and implementing affect in artificial intelligence. The first paper proposes a relational framework for affective computing, focusing on interactional fields within vocal dynamics rather than isolated emotional states. The second paper presents a computational implementation of a goal-directed theory of affect, where affect emerges from the interplay of discrepancy detection and action selection in agents. Both studies aim to move beyond descriptive models towards more mechanistic and integrated understandings of affect in AI. AI

IMPACT These papers propose novel frameworks for understanding and implementing affect in AI, potentially leading to more nuanced and interactive artificial agents.

RANK_REASON Two academic papers published on arXiv detailing new computational approaches to affect in AI.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

AI research explores new computational models for affect and interaction · 2 sources tracked

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Two academic papers published on arXiv detailing new computational approaches to affect in AI.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Cy Gorman, Yihang Yao ·

    Shifting Relational Paradigms for Affective Computing: Affective Resonance, Vitality Affects, and Vocal Interaction Fields

    arXiv:2609.09864v1 Announce Type: new Abstract: Affective computing has largely followed an individual-state paradigm, extracting discrete emotion labels or arousal/valence from isolated speakers. We argue this framing is incomplete for interaction. Drawing on affective resonance…

  2. arXiv cs.AI TIER_1 English(EN) · Bernhard Hilpert, Tam\'as Sz\H{u}cs, Joost Broekens, Agnes Moors ·

    A Computational Implementation of a Goal-Directed Theory of Affect

    arXiv:2609.06654v1 Announce Type: new Abstract: Computational modeling of emotion has long faced a tension between descriptive, "snapshot-based" appraisal models and granular, signal-driven architectures that often lack appropriate psychological grounding. This paper addresses th…

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