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Affective Computing: Agents With Emotion. Victor C. Hung University of Central Florida – Orlando, FL EEL6938: Special Topics in Autonomous Agents March 29, 2007. Agenda. Introduction Highlighted Projects Affective Cognitive Learning & Decision Making Questions. Introduction.

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Affective Computing: Agents With Emotion

Victor C. Hung

University of Central Florida – Orlando, FL

EEL6938: Special Topics in Autonomous Agents

March 29, 2007


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Agenda

  • Introduction

  • Highlighted Projects

  • Affective Cognitive Learning & Decision Making

  • Questions


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Introduction

  • Affective Computing relates to, arises from, or deliberately influences emotion or other affective phenomena

    • Engineering, computer science with psychology, cognitive science, neuroscience, sociology, education, psychophysiology, ethics …

  • Emotion is fundamental to human experience

    • Cognition

    • Perception

    • Learning

    • Communication

    • Rational decision-making


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Introduction

  • Technologists have largely ignored emotion

    • Affect has been misunderstood

    • Hard to measure

  • MIT Media Lab: Affective Computing

    • http://affect.media.mit.edu

    • Develop new technologies and theories

      • Understanding affect and its role in human experience

    • Restore a proper balance between emotion and cognition in the design of technologies for addressing human needs


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Introduction

  • Issues in affective computing

    • Communication of affective-cognitive states to machines

    • Techniques to assess frustration, stress, and mood indirectly

    • Make computers can be more emotionally intelligent

    • Personal technologies for improving self-awareness of affective states

    • Emotion’s influences personal health

    • Ethics


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Highlighted Projects

  • Affective-Cognitive Framework for Machine Learning and Decision-Making

    • Emotion’s role in learning and decision making

  • Digital Story Explication as it Relates to Emotional Needs and Learning

    • Emotional interaction in child learning

  • ESP - The Emotional-Social Intelligence Prosthesis

    • Aid for the emotionally-impaired


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Highlighted Projects

  • Fostering Affect Awareness and Regulation in Learning

    • Combat frustration during the learning process

  • Machine Learning and Pattern Recognition with Multiple Modalities

    • Emotional sensor data fusion

  • Ripley: A Conversational Robot

    • Human-robot interaction platform through language and visual perception modalities


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Affective-Cognitive Learning & Decision Making

  • (2006) Ahn and Picard’s “Affective-Cognitive Learning and Decision Making: The Role of Emotions”, The 18th European Meeting on Cybernetics and Systems Research

    • Framework for learning and decision making

    • Inspired by neural basis of motivations and the role of emotions in human behavior

      • Affective biases

      • Loss aversion

      • Effect of mood on decision making


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Affective-Cognitive Learning & Decision Making

  • Affective biases

    • Two-armed bandit


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Affective-Cognitive Learning & Decision Making

  • Loss aversion

    • Prefer avoiding losses than acquiring gains


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Affective-Cognitive Learning & Decision Making

  • Effect of mood on decision making

ANGER

Optimism about the future

HAPPINESS

Optimism about the present

Pessimism about the future

FEAR

Pessimism about the present

SADNESS


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Affective-Cognitive Learning & Decision Making

  • A motivational value (reward)-based learning theory:

    • Extrinsic value from the cognitive (deliberative and analytic) systems

    • Intrinsic value from multiple affective systems such as Seeking (Wanting), Fear, Rage, and other circuits

  • Probabilistic models

    • Cognition (cognitive state transition)

    • Multiple affect circuits (Seeking, Joy, Anger, Fear, ...)

    • Decision making model

  • Previous knowledge can be incorporated for expecting the consequences of decisions (or computing the cognitive value)


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Affective-Cognitive Learning & Decision Making


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Affective-Cognitive Learning & Decision Making

  • The Decision-Making Model

    • Cognitive state (c)

    • Affective state (a)

    • Decision (d)


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Affective-Cognitive Learning & Decision Making

  • Affective seeking value =

    • Valence = decided by the mean of the filtered values for the reward samples

    • Arousal = uncertainty of the reward sample distribution (modeled as standard deviation)

  • Complete decision-making expression:

  • Non-affect agent has only the cognitive component


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Affective-Cognitive Learning & Decision Making

  • Affective agent vs. Non-affect agent


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Affective-Cognitive Learning & Decision Making

  • Influence of an outlier on the cognitive values and the valence values


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Affective-Cognitive Learning & Decision Making

  • Affective component less sensitive to outliers than cognitive component

  • Affective Cooling: Agreement between two components

    • More likely to follow the decision by the cognitive component (Exploitation)

    • Value of the induced inverse temperature parameter increases

    • Humans using cognition in decision-making

  • Affective Heating: Conflict between two components

    • Less likely to follow the decision by the cognitive component (Exploration)

    • Value of the inducedinverse temperature parameter decreases

    • Humans depending on emotion in decision-making


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Affective-Cognitive Learning & Decision Making

  • 10-armed bandit tasks


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Affective-Cognitive Learning & Decision Making

  • Too much or too little affect impairs learning

    • Excessive learns faster, but not good for long-term

    • Insufficient better for long-term, but slow


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Affective-Cognitive Learning & Decision Making

  • Results and Conclusions

    • Framework enhancements

      • Model other affect circuits

      • Incidental influences on decision making

      • Use of prior knowledge for expecting cognitive outcomes ・

    • Affective bias

      • Helps automatically regulate exploration and exploitation

      • Speed up learning without sacrificing decision quality

    • This framework might mimic well-studied human behavior

      • Risk aversion

      • Effects of mood on decision making

      • Self-control


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Questions?


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