Marital Agent Trait-Based Emotion System

1. Marital Agent Trait-BasedEmotion System • System collects information about a pre-marital couple. • Use questionnaires to determine • Personality- IPIP NEO • Relationship concerns (Gottman) • Goals with emotion vectors • Model couple in negotiation V.H. Allan: Utah State University

2. Idea: What if we programmed an agent to act like a person in a social situation? Could a person learn something valuable by seeing his behavior? Could a person benefit by replaying the situation using a new set of behaviours? V.H. Allan: Utah State University

3. IPIP Personality Survey (Goldberg) V.H. Allan: Utah State University

4. IPIP-NEO Narrative Report – (Validated Survey) • EXTRAVERSION 94 • Gregariousness 91 • Assertiveness 82 • Activity Level 97 • Excitement-Seeking 49 • Cheerfulness 80 • AGREEABLENESS 81 • Trust 87 • Morality 63 • Altruism 88 • Cooperation 73 • Modesty 25 • Sympathy 77 Computed from 120 questions Includes explanation of Traits V.H. Allan: Utah State University

5. IPIP-NEO Narrative Report (cont) • NEUROTICISM 6 • Anxiety 0 • Anger 16 • Depression 16 • Self-Consciousness 39 • Immoderation 8 • Vulnerability 29 • OPENNESS TO EXPERIENCE 35 • Imagination 65 • Artistic Interests 18 • Emotionality 83 • Adventurousness 9 • Intellect 86 • Liberalism 4 • CONSCIENTIOUSNESS 84 • Self-Efficacy 96 • Orderliness 36 • Dutifulness 87 • Achievement-Striving 83 • Self-Discipline 87 • Cautiousness 7 V.H. Allan: Utah State University

6. Interaction Style Questions John Gottman’s Work • I soften the conflict by constructively focusing on feelings first (i.e., "This is how I feel when...") and then moving on to the specific issue or complaint. • I focus on one specific issue at a time and seek to resolve it before moving on to another issue so the conflict doesn't degenerate into a mudslinging contest. • I focus on the present issue rather than bring up issues from the past as weapons to use in an attempt to gain power and control over the situation or another person. • I think win/win and understand that if one person loses the argument, then both people in the relationship lose. • I soothe my partner through speaking non-defensively, validating his or her perceptions and feelings, or by using humor. • I seek to resolve the specific issue as soon as possible in order to avoid experiencing ongoing resentment, frustration, or hurt feelings. V.H. Allan: Utah State University

7. Relationship Goal Questionnaire(Validity Untested) • I get satisfaction in making my partner happy. • I get satisfaction in controlling our relationship. • Getting my own way is important. • Having a positive interaction is important to me. • Being validated is important to me. V.H. Allan: Utah State University

8. Program Agents with Personality and Emotion • Bob and Alice are considering marriage. • Evaluate their personalities • Agent Bob and Agent Alice • Give Agents a problem and view how they negotiate. V.H. Allan: Utah State University

9. Goal: Create better communication “My wife and I had words, but I never got to use mine.” -Fibber McGee V.H. Allan: Utah State University

10. Goal: Create more realistic expectations • Marital happiness is a function of both expectation and actual relationship quality. V.H. Allan: Utah State University

11. Marital Research • How a couple differs is not so important (as there will always be differences). • What is important is how they deal with those differences. • This research seeks to expose differences. V.H. Allan: Utah State University

12. Several studies suggest • Researchers can predict which marriages will end in failure from information gathered before the couple marries. • Tell people if they are at substantially greater risk for divorce • Told couples argue most about children and money, but some believe how they argue is most important. V.H. Allan: Utah State University

13. Goal Database Plan Generator Plan Beliefs Inference Engine History Emotion Transformer Behavior Generator Personality Reactive Response Generator External Communication Conversation Partner Control Flow Data Flow V.H. Allan: Utah State University

14. Planner Generates Interaction • Simple, hierarchical ordered planner • Implemented in Prolog • An agent calls the planner with a list of goals to obtain the plans. • The agent calls the prolog function • plan ([a, b, c], [], Plans) • 1st argument: a, b and c are the goals. • 2nd argument: specifies the initial list of plans to start with • 3rd argument: Accumulator for the resulting plans. V.H. Allan: Utah State University

15. Who determines the starting goal-list on which the planner works to generate plans? • The human user (useful for testing agents’ behavior on several kinds of goals) • An automatic goal initializer – • a simple piece of prolog code • evaluates the preferences V.H. Allan: Utah State University

16. Three phases of planner • Environment Setting phase • Fact retrieval phase • Presentation planning phase V.H. Allan: Utah State University

17. Dynamic re-planning • The basic idea is to plan for many expected situations and when an unexpected situation arises, modify the database and re-plan. • Possible extensions to planner: Make it stochastic to simulate human indeterminism. Probabilities are determined by personality, emotion, and history. V.H. Allan: Utah State University

18. Agent Database: • For each agent: • Goals • Beliefs • History • Personality • Miscellaneous V.H. Allan: Utah State University

19. Decomposing goal - precondition • showPower(Proposal, Activity, ActivityName, ActivityActors, ActivityType, Time), • [ logic(X), X < logicCutoff, • polite(Y), Y < politeCutoff, • likes(Activity), enjoys(ActivityType), • not(partnerLikes(Activity)), • not(partnerEnjoys(ActivityType)), • activityName(Activity,ActivityName), • activityActors(ActivityName,ActivityActors), • free(Time) • ], V.H. Allan: Utah State University

20. Plan - components • [ • propose(Activity, ActivityName, • ActivityActors, ActivityType, Time), • [acknowledge(accept(Activity, ActivityName, • ActivityActors, ActivityType, Time)); • accuse(reject(Activity, ActivityName, • ActivityActors, ActivityType, Time))] • ] • ). V.H. Allan: Utah State University

21. Express interaction patterns as regular expression • propose (reject cope)* (accept react)? • * zero or more occurrences • ? zero or one occurrences V.H. Allan: Utah State University

22. Express interaction as stochastic context free grammar • Used as a generator. • Grammar to control options • Stochastic to give probability to actions. • Probability depends on history, personality, interaction patterns. • Dynamically evaluated V.H. Allan: Utah State University

23. A very simple plan might look like: • // Environment setting phase • setHonesty(minHonestyValue), • setAffection(minAffectionValue), • setPride(maxPrideValue), • // Fact Retrieval phase • getFreeTimes(self, FreeTimes), • getFreeTimes(partner, FreeTimes) • getActivity(Activity, FreeTimes), • not PartnerLikes(Activity), • // Presentation planning phase • propose(Activity), • acknowledge(accept(propose(Activity)), • accuse(reject(propose(Activity)), • replan(other). V.H. Allan: Utah State University

24. Interaction Patterns • speaker/listener (take roles) • criticism • defensiveness • contempt • stonewalling (listener withdrawal emotionally and perhaps physically) • kitchen sink (prior complaints brought up) V.H. Allan: Utah State University

25. Emotions to expression • Emotions passed as an internal form. • complete range of values • no need to parse expression for meaning • can filter so not “transparent” • Expressions are generated for GUI • Difficulty in mapping large number of emotions into expression. V.H. Allan: Utah State University

26. Mapping – rejection phrases • Sorry. • I can’t. • I can’t. Maybe some other time • I’d rather not. • No. • I won’t • Absolutely not. • That is ridiculous. I won’t consider it. V.H. Allan: Utah State University

27. Mapping - motivations • Consider various reasons for saying no • Conflict. • Possible conflict • No interest in going to event. • Too busy. • Anger over other rejections • Feel person is inconsiderate V.H. Allan: Utah State University

28. Mapping personalities • How does personality affect answer? • aggressive • trusting • cooperative • cautious • depressed • anxious • angry V.H. Allan: Utah State University

29. In theory, mapping Personality Result History output expression Plan Very complex mapping V.H. Allan: Utah State University

30. Regular expression • Rejection: reject+ explanation* judgment* soften? counter-proposal? • + one or more • * zero or more • ? zero or one • Repetition determined by parameters V.H. Allan: Utah State University

31. Explanation • because of ‘something you have done (I’m mad at you, I don’t want to spend time with you, I would rather be with my friends/family)’ • because it is (ridiculous, dumb, self-centered, unworkable) • because of ‘some situation’. • because I have a conflict • because of prior history • I am so sorry. • Maybe another time • I am just too busy for you. • I am just too busy. I should make time for my good friends. V.H. Allan: Utah State University

32. Judgment: • You have such good ideas. • You are so thoughtful to have asked. • That does sound fun. • You always want to do things I don’t like. • You never consider my feelings. • Why did you think I would want to do that? V.H. Allan: Utah State University

33. Softening: • You have so many good traits • I’ve heard really good things about you • I remember when we had a good time together. V.H. Allan: Utah State University

34. Counter proposal: • Maybe another time/day • Maybe another activity • Maybe we should do some other thing I know you like. • Maybe we should do something we both like. • Maybe we should do something only I like. V.H. Allan: Utah State University

35. Grammar may be viewed as a stochastic finite state machine Explanation reject Judgment • Rejection: reject+ explanation* judgment* soften? counter-proposal? reject soften counter V.H. Allan: Utah State University

36. Thus, responses might vary from: • No. Maybe another time • I am so sorry. You have such good ideas. Maybe we should go bowling. Maybe we should go golfing. Maybe we should go tomorrow. Maybe we should go Friday. • No. No. No. I won’t. I am too busy for you. You never consider my feelings. V.H. Allan: Utah State University

37. Modeling Emotions • Emotions are important in giving Disney characters the illusion of life. • Believability vs realism: may be better to use simplified, exaggerated characters. V.H. Allan: Utah State University

38. How to Combine Emotions • Winner take all – ignore all but the highest intensity emotion • Additive – but may be confusing to model joy and sadness simultaneously • Logarithmic: log(2emotion1 + 2emotion2) • Focus – kicking example V.H. Allan: Utah State University

39. How created? • Emotions are tied to goals (through personality survey). When a goal is achieved, attached emotions are generated. • Factors: surprise, importance of goal, difference in emotion felt with success or failure of same goal. (e.g., goal: to have companion) V.H. Allan: Utah State University

40. Goals • Intensity • Chance of succeeding • Emotions generated when fail • Emotions generated when chance of succeeding increases/decreases. V.H. Allan: Utah State University

41. What kind of transformations? • Decay – all at same rate? • Combine • Filter • Idea: create an algebra of emotions through matrix manipulation V.H. Allan: Utah State University

42. What effects emotions? • Personality – each personality type will express emotions in its own way. • relationships: affect what emotions are felt and how strongly • memory: previous experiences (Were you angry when the first telemarketer called?) V.H. Allan: Utah State University

43. Challenges • Cardboard personalities? • How create grammar? • IPIP survey validated • Gottman research well-respected, but is it valid for self-reporting? • Goal data – unclear what goals to even ask about Held to a higher standard – not just entertaining. • How do we test it? (subjective tests?) V.H. Allan: Utah State University

44. After a quarrel, a husband said to his wife, “You know, I was a fool when I married you.” The wife replied, “Yes dear, but I was in love and didn’t notice.” Much testing is needed. V.H. Allan: Utah State University