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Emotions: a computational semiotics perspective

Explore the evolution of Machine Emotion Quotient (MEQ) and the semiotics in AI from a groundbreaking study by Rodrigo Gonçalves, Ricardo Gudwin, and Fernando Gomide. Learn about the cognitive representations of emotions and the interplay between mind, body, and emotions in an intelligent agent. Discover how emotions influence reasoning processes and the significance of somatic markers in the evaluation of mental images.

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Emotions: a computational semiotics perspective

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  1. Emotions: a computational semiotics perspective Rodrigo Gonçalves, Ricardo Gudwin, Fernando Gomide Electrical and Computer Engineering School (FEEC) State University of Campinas (UNICAMP) CP.6101 - CEP 13083-970 Capinas, SP, Brasil

  2. MEQ (Machine Emotion Quotient) Evolution MEQ ? Semiotics in AI AI/Cybernetics Soft computing Damasio's book 80's 90's The beginning - big dreams leaded to big disappointments Cognitive representations of emotions instead emotions itself Emotions not as a psychological state of the soul - a physical phenomena

  3. Mind & Body • Our mind is physically associated with our body through our brain Mind model Mind+body model + ¹ Body model Intelligent agent

  4. Imagetic and distributed nature of thinking • There is no centralized big screen where our thoughts are projected. • We process each kind of sense in physically different and distributed location. • Two different types of mental images: • Perceptual - generated by our sensors or by dispositive images • Dispositive - prototypical image that hold rules to reconstruct perceptual images. Perception Perceptual images Learning Backfire Dispositive images

  5. Two basic categories of emotions: Primary innate often related to self-preservation and reproduction. Unconsciousness level Secondary not innate (learning) (Un)consciousness level Emotions (I) • Feelings ¹ Emotions • Emotions - dispositive image that affects the body internal state in response to perceptive images • Feeling - the perception that the body state has changed

  6. Intuition = Somatic Mark a value of desirability (an apraisive knowledge) attributed to any mental image in an unconsciousness level mechanism called somatic marker Somatic marker continuously analyses the body state and mental images calculating and attributing a desirability value based on basic instincts. Emotions (II) • Emotion is able to change the body internal state and consequently affects how the brain process others mental images • changing the performance of the cognitive mechanism • attributing an intuition to another mental image (somatic mark)

  7. Reason uses the intuition and consequently the emotion mechanism drastically decrease the search space for complex problems Emotions x Reason • Instincts (reactive responses) are dispositive images that generate behavior and/or emotions • characteristics of the species • related to auto-preservation • Reasoning might be considered as an instinctive process.

  8. Somatic agent • Six independent and unsynchronized modules communicating through a blackboard-like memory • sensing • actuator • body modeler • somatic marker • rational processor • dispositive memory • Communication through a blackboard-like memory • mental images as elemental communication data unit • modules are both image producers and consumers • all messages (mental images) are posted in the working memory and all modules may access it Work memory Image producers & consumers

  9. Mental image • Elementary communication data unit in somatic agents • Composite knowledge • set of knowledge units • the meaning of the set is different of the sum of meaning of each part • can be classified into the elementary taxonomy (based on the semantics of the hole set of knowledge)

  10. Somatic agent hierarchy • Object oriented structure based on the knowledge taxonomy • allows a blackboard-like implementation • Attributes: • type; • desirability; • time stamp; • mean life; • data • Relations • “created_by”; • “created_from”; • consequence pointer; • Methods • compareTo

  11. Mental image hierarchy • Follows the knowledge taxonomy • Object • Sensorial • Occurrence

  12. Somatic agent image generators (and consumers) • Sensor • Body modeler • Somatic marker • Dispositive memory • Actuator • Rational processor

  13. Creates perceptive sensorial images based on data obtained in the external world and posts them into the working memory Read & concatenate perceptive sensorial images from working memory concatenate and create another sensorial image with higher level sensorial data Monitors the system body Body model perceptive image that holds a rhematic object specific knowledge Body modeler reads sensorial images in the working memory, processes it, and actualizes the body model image Body modeler Sensor Actuator • Capture mental images with prescriptive content in the working memory and use them to act in the external world

  14. Somatic marker • Calculate a degree of desirability to every mental image in the system • Used by the rational processor as some kind of intuition about an image and is calculated using innate rules or by image similarity (using compareTo method) • It is not an emotions. It is only a judge value given to an image based on the somatic state and innate knowledge • Unconscious level • the rational processor of the somatic agent does not have any control over it and it accesses any mental image produced in the system

  15. Dispositive image&Dispositive memory • Dispositive image • similar to perceptual image. It holds generic knowledge instead of a specific one • it might be triggered generating perceptual images (associative memory) • Two types: • ordinary • emotional  emotions! • Dispositive memory • Module that holds a collection of dispositive images

  16. Conscious behavior generation Higher levels behavior. Most of lower level behaviors, like reactive ones, are responsibility of the dispositive memory module Semiotic cycle Consumes images performs abduction, induction and deduction over them, creating new images Integrated with emotions mechanism the implementation of the rational processor should consider the desirability value calculated by the somatic marker mechanism Rational processor

  17. Somatic Agent • Might be integrated using Object Networks

  18. Conclusions • The emotion must be seen not as a heuristic that leads to an optimal solution to any problem but as a process, that turns complex tasks possible. In this paper we show how the real concept of emotions can be captured and implemented. For that, we used some concepts of computational semiotics and Damasio’s theory of emotions. • Currently we are working in an application example that will be a subject for future publications.

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