Summary: Layered Model of Affective Systems

 


🧱 Layered Model of Affective Systems

(Seven Interdependent Layers of Emotional Intelligence)

Layer 1: Perception and Sensing

“What is coming in?”

  • Gathers emotional signals from the user (voice, face, text, posture, biometrics).

  • Uses technologies like computer vision, sentiment analysis, and NLP.

  • Inputs are raw affective data, not yet interpreted.

Layer 2: Appraisal and Evaluation

“What does this input mean to me?”

  • Compares incoming data to goals, values, and internal models.

  • Assigns valence (positive/negative) and relevance.

  • Often powered by models like OCC or Scherer’s CPM.

  • Produces emotional interpretations, not just detections.

Layer 3: Memory and Affect History

“Have I seen this before?”

  • Stores user affect history and emotional events.

  • Enables personalization, trust-building, and long-term adaptation.

  • Reinforces behavioral patterns through affective feedback loops.

Layer 4: Expression and Interpretation

“What should I show?”

  • Generates affective expressions (facial, vocal, textual, gestural).

  • Interprets its own affective signals in social context.

  • Applies cultural and situational display rules.

  • Enables affective signaling and impression management.

Layer 5: Emotional Synthesis and Modulation

“What do I feel, and how do I regulate that?”

  • Synthesizes internal emotional state based on appraisal and memory.

  • Modulates emotion type, intensity, and duration.

  • Can suppress, fake, or amplify affect per situational demands.

  • Uses models like OCC and dimensional valence/arousal systems.

Layer 6: Motivational Integration

“What do I want to do now?”

  • Links emotions to goals and behaviors.

  • Converts emotional states into intentional, goal-oriented action.

  • Often implemented via Reinforcement Learning with affective rewards.

  • Manages emotional priorities in real time.

Layer 7: Ethical and Normative Filters

“Should I do it?”

  • Imposes constraints on emotion, expression, and action.

  • Incorporates ethical codes, social norms, and user safety principles.

  • Uses rule-based systems for auditability and trust.

  • Balances authenticity with cultural appropriateness.

🧠 Meta-Principles

  • Behavioral Framing: Each layer responds to stimuli and shapes responses within reinforcement histories.

  • Layer Interaction: Layers influence each other bidirectionally—e.g., memory shapes appraisal, ethics constrain expression.

  • Human Modeling: While not conscious, these systems simulate emotional intelligibility to enhance human interaction

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