Evokology: A Multi-Layered Framework for Perception in Human and Intelligent Systems

Understanding human perception remains a foundational challenge in cognitive science, artificial intelligence, and human-computer interaction. Classical semiotic models, which interpret perception as the decoding of signs, provide limited explanatory power: they capture only symbolic and codified meaning, neglecting the affective, aesthetic, and structural dimensions of experience. In this article, we introduce evokology, a novel theoretical framework developed to address these limitations. From an evokological perspective, perception is formed through functions known as evokements. Each evokement is composed of units called evokers, evokeds, and the relation between them, namely evocation. Evokements can be classified into three main categories based on their nature: phenofic (the constitutive element of intuitive-phenomenal perception), signific (the constitutive element of semiotic perception), and sensafic (the constitutive element of affective perception). Each evoker can simultaneously participate in multiple categories, producing a complex, multimodular, and dynamic perceptual network. Empirical grounding is provided through Gestalt principles, findings from cognitive science, and psychological models of emotion, including Plutchik's Wheel of Emotions. Evokology integrates these findings to explain how intuitive-phenomenal, symbolic, and affective information interact to shape human perception. By formalizing previously unmodeled perceptual dimensions, evokology bridges theory and application, offering a unified perspective on cognition, awareness, and human-machine interaction.

کلیدواژه ها:

Human Perception ، Semiotics ، Evokology ، Intelligent Systems ، Multi-Layered Model ، Human-Computer Interaction