Emotionally Responsive Robotic Avatars in Virtual Worlds

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How Daden have implemented Wolverhampton University's E-AI architecture to drive avatars in Second Life and model emotional response

Transcript of Emotionally Responsive Robotic Avatars in Virtual Worlds

  • 1.Emotionally Responsive Robotic Avatars as Characters in Virtual Worlds David Burden Daden Limited Stuart Slater University of Wolverhampton

2. Evolving UI Paradigms Teletype Character VDU Windows Audio-Visual Virtual Worlds 3. Non-Player Characters (NPCs)

  • Task focussed
  • Usually no life beyond the user
  • Privileged access to information
  • Common in MMORPGs, less common in Virtual Worlds

4. Virtual Worlds

  • Socially focussed
  • Can be persistent
  • Access the world on the same basis as a human
  • Visually can be identical to a human user's avatar
  • Roles include receptionists/greeters, salesmen, actors, tutors

5. Emotional Chatbots

  • Given that computer controlled avatars (robotars) can access all of the gesture and emotional expressions of a human controlled avatar, how important is the use of such emotions with computer controlled avatars?

6. Altair Robotar Architecture libsecondlife altair #2 Second Life Servers ASML/ AAML via web service Perl API Bus Human User BotIF altair #1 Other Engines Emotion Engine Navigation Engine Discourse AIML Chatbot Engine Web Services Server (on web) (Perl) PC or Server (on web) (C#) SL Interface Discourse RDF Engine 7. E-AI Architecture

  • Developed by University of Wolverhampton
  • Followed assessment of CogAff7, Emile8,SOAR9 and Tok10
  • Grounded in psychology and psychology research and models
  • Intended for developers who already have a broader bot architecture

8. Emotions Modelled

  • Happy
  • Sad
  • Fear
  • Disgust
  • Anger
  • Surprise/Startle

9. E-AI Architecture 10. Previous Implementations

  • Quake-3 combat bots
  • Over 300 combat situations
  • Got around 20% less kills, won a below average (almost half) number of matches
  • Results clearly supported the assumption that the emotionally enhanced bots, performed less well in combat situations.
  • Lack of combat effectiveness was partly attributed to the e-Bot running away from combat situations when experiencing fear, and often froze for a second (startle response) when an attacking bot came round a corner.

11. E-AI Architecture with Altair Object and avatar appearance/ disappearance (ASML) 1. Surprise & Startle vs EAD 2. Explicit vs AIML 3. Implicit vs EAD/Chat Lookup => AEML Avatar expressions/ gesture/movement/chat (AAML) Not yet modelled Not yet modelled Fuzzy mixing of emotional states => AEML Reason for last state stored, and accessible from AIML 12. Additional Features

  • High Road vs Low Road
    • Low-road (gut) response implemented close to avatar in C#/BotIF
    • High-road (considered) response implemented in AIML, other side of a web service
  • Moods
    • Each new emotion effects the on-going mood
    • Moods have half-lives and decay over time
  • Habituation
    • With repeated exposure the response to an emotional stimulus can decrease/increase
    • Each EAD trigger has an habituation factor

13. Learnt Behaviour

  • Manual EAD Creation
    • Time consuming
    • No guarantee objects will have the right name
    • Not scalable to true AI
  • Bot Learning
    • Programme only fundamental responses, eg:
      • Be fearful of things that hurt you
      • Like things that give you money
    • Bot then builds EAD as it experiences things in the world

14. Demonstration Video 15. User Evaluation - Provisional

  • 2 sessions of 10 16 students (Computer and Games courses)
  • Session 1:
    • Evaluate robotar with/without emotional gestures/expressions, but same chat responses
    • Most noted some difference
    • Majority preferred emotional bot
  • Session 2:
    • Evaluate robotar with emotional expression and chat responses and without expression/chat responses
    • Almost all noted some difference
    • Clear majority preferred emotional bot

16. Conclusions

  • Virtual world robotars provide a greater challenge (and opportunity) than game NPCs
  • The E-AI architecture is a useful way of modelling emotions in avatars
  • E-AI can be used to support habituation and learnt behaviour
  • Initial user evaluation suggests that users prefer interacting with a more emotional avatar

17. Emotionally Responsive Robotic Avatars as Characters in Virtual Worlds David Burden Daden Limited Stuart Slater University of Wolverhampton [email_address] [email_address]