1. Anticipation and Emotion: a low-level approach to Believability
Carlos Martinho, João Gonçalves, Ana Paiva
Instituto Superior Técnico
MindRACES, First Review Meeting, Lund, 11/01/2006

2. MindRACES, First Review Meeting, Lund, 11/01/2006
Outline
IST MindRACES Scenario
Aibo in the domotic household
Low-level Anticipatory Affective Architecture
Test Environment: Aini
Integrates Anticipation and Attention
Integrates Anticipation and Emotion
Integrates Uncertainty as Meta-Anticipation
Preliminary Evaluation of the Architecture
Future Work in MindRACES
MindRACES, First Review Meeting, Lund, 11/01/2006

3. MindRACES, First Review Meeting, Lund, 11/01/2006
IST Scenario
Scenario 1 - Task 3: “Looking for an object”:
Takes place in a household environment where Aibo, the synthetic dog, “lives”. Several distractors, will be added to difficult the task and provide with opportunities for Aibo to “play in character” and be evaluated in terms of believability.
MindRACES, First Review Meeting, Lund, 11/01/2006

4. MindRACES, First Review Meeting, Lund, 11/01/2006
IST Scenario Context
Our Competences:
Provide with an anticipatory affective component, a low-level approach that provides with believable behaviour while an agent is searching for an object.
Simulation only. Need components for real-world integration.
Missing Links:
Learn to find an object in an occluded environment (IDSIA fovea + UW-COGSI learning strategies).
High level anticipatory affective cognitive reasoning component (ISTC-CNR BDI extension with expectation) for dealing with unplausibility, curiosity, cautiousness...
Using reasoning by analogy to complement the search process (NBU).
MindRACES, First Review Meeting, Lund, 11/01/2006

5. MindRACES, First Review Meeting, Lund, 11/01/2006
Virtual AIBO Toolbox
Main purpose is to assess if the physical restrictions of Sony AIBO are adequate for the expression of believable behaviour.
MindRACES, First Review Meeting, Lund, 11/01/2006

6. AIBO Domotic Environment
AIBO sleeps near the children while they play in the living room when it senses the arrival of their father from work. Aibo will run to the front door and starts barking, anticipating the arrival of the owner.
MindRACES, First Review Meeting, Lund, 11/01/2006

7. AIBO Domotic Environment
AIBO will monitorize the domotic system and will give clues on what relevant events are occuring inside the household.
MindRACES, First Review Meeting, Lund, 11/01/2006

8. Low-Level Architecture (D5.1)
Sensor
Effector
Emotivector
(lower-cognition anticipatory affect)
SENSATIONS
Agent Processing (BDI extension)
(higher-cognition anticipatory affect)
EMOTIONS
MindRACES, First Review Meeting, Lund, 11/01/2006

9. AINI Environment Testbed
anticipatory believability
MindRACES, First Review Meeting, Lund, 11/01/2006

10. MindRACES, First Review Meeting, Lund, 11/01/2006
The Word Puzzle Game
MindRACES, First Review Meeting, Lund, 11/01/2006

11. MindRACES, First Review Meeting, Lund, 11/01/2006
Anticipation ?
0.4
0.3
0.2
time
MindRACES, First Review Meeting, Lund, 11/01/2006

12. MindRACES, First Review Meeting, Lund, 11/01/2006
Anticipation
Expected Value
0.5
0.4
0.3
0.2
time
MindRACES, First Review Meeting, Lund, 11/01/2006

13. Anticipation and Attention
Posner 1980
Müller and Rabbit 1989
Expected Value
0.5
0.4 
0.3
Sensed Value
0.2
0.2
time
SURPRISE = automatic reaction to a mismatch (Castelfranchi 2005)
MindRACES, First Review Meeting, Lund, 11/01/2006

14. MindRACES, First Review Meeting, Lund, 11/01/2006
Attention in Action
[demo]
MindRACES, First Review Meeting, Lund, 11/01/2006

15. Anticipation and Emotion?
0.4
0.3
0.2
time
MindRACES, First Review Meeting, Lund, 11/01/2006

16. Anticipation and Emotion
Some signals may have a search value
MindRACES, First Review Meeting, Lund, 11/01/2006

17. Anticipation and Emotion
search
1.0
current distance ?
0.4
0.3
0.2
time
MindRACES, First Review Meeting, Lund, 11/01/2006

18. Anticipation and Emotion
search
1.0
expected
distance
current distance
0.5
expected
reward
0.4
0.3
0.2
time
MindRACES, First Review Meeting, Lund, 11/01/2006

19. Anticipation and Emotion
search
1.0
sensed
distance
sensed
punishment
0.4
0.3
0.2
0.2
time
MindRACES, First Review Meeting, Lund, 11/01/2006

20. Anticipation and Emotion
Expectated Qualia vs Sensed
Surprise (S)
Positive Increase (S+)
Positive Reduction ($+)
Negative Increase (S-)
Negative Reduction ($-)
MindRACES, First Review Meeting, Lund, 11/01/2006

21. Anticipation and Emotion
Harlow and Stagner (1933)
Emotion versus sensation
Young (1961)
Emotion as process in hedonistic continuum
Hammond (1970)
Existence / absence of stimuli
Millenson (1967)
Intensity versus name
Example of Sensation: $+
Harlow and Stagner - discontentment
Hammond - Distress
Millenson - negative unconditioned stimulus
MindRACES, First Review Meeting, Lund, 11/01/2006

22. MindRACES, First Review Meeting, Lund, 11/01/2006
Emotions in Action
MindRACES, First Review Meeting, Lund, 11/01/2006

23. Uncertainty and Salience Management
Emotivector Salience Management Strategies:
Winner takes-all: idle and restrictive
Resource ordering: wasted in low relevance
Treshold limit: which value to use?
Meta-Anticipation
MindRACES, First Review Meeting, Lund, 11/01/2006

24. Uncertainty and Salience Management
Model( M )
Error Prediction = Uncertainty
Model( S )
System S
Environment E
Meta-anticipatory System
MindRACES, First Review Meeting, Lund, 11/01/2006

25. Uncertainty and Salience Management
predicted
error
0.4
0.3
0.2
time
MindRACES, First Review Meeting, Lund, 11/01/2006

26. Uncertainty and Salience Management
non-relevant
signal
0.4
0.3
relevant
signal
0.2
time
Introduces uncertainty as error-prediction (resilient to white noise - Schimidhuber)
Extension to 9 sensations (using neutral-based sensations)
MindRACES, First Review Meeting, Lund, 11/01/2006

27. MindRACES, First Review Meeting, Lund, 11/01/2006
Prediction
Comparative Evaluation of different algorithms:
Polynomial Extrapolation (cubic curves)
Error-Based learning
Kalman filtering
Statistical Limitation
PID based prediction
MindRACES, First Review Meeting, Lund, 11/01/2006

28. MindRACES, First Review Meeting, Lund, 11/01/2006
Prediction Winner
Kalman-filtering simplification + 2-phase recirculation algorithm + statistical limitation
MindRACES, First Review Meeting, Lund, 11/01/2006

29. Evaluation: Word Puzzle Scenario
MindRACES, First Review Meeting, Lund, 11/01/2006

30. Preliminary Evaluation
Believability-oriented evaluation
Pre-evaluation with 10 representants of 5 user-groups:
from 5 to 79 years-old of both sexes
different familiarities with computer systems
Divided the experiment in 2 fases:
Training: navigation, attention, emotion
Word Puzzle: 2 control, 1 emotivector-based, 1 common sense algorithm used in games
All 10 subjects succeeded at the task but (surprisingly) only with emotivector-based approach!
MindRACES, First Review Meeting, Lund, 11/01/2006

31. MindRACES, First Review Meeting, Lund, 11/01/2006
Future Work
Evaluation of AINI scenario foir believability with users
Assert relevance for the community
Implementation of architecture in AIBO
Evaluation of domotic scenario for believability with users
Integration of high-level Anticipatory Affect (ISTC-CNR)
Integration of real-world search functionality: IDSIA (fovea), UW-COGSI (search) and NBU (analogy)
Evaluation of the integration (real time constraints)
MindRACES, First Review Meeting, Lund, 11/01/2006

32. MindRACES, First Review Meeting, Lund, 11/01/2006
Questions?
MindRACES, First Review Meeting, Lund, 11/01/2006