On TAMEing Robots: A Framework for Affective Robotic Behavior

1. On TAMEing Robots: A Framework for Affective Robotic Behavior GVU Brown Bag Presentation Lilia Moshkina Moshkina, L., and Arkin, R.C., On TAMEing Robots, Proc. IEEE International Conference on Systems, Man and Cybernetics, Oct. 2003

2. Preliminaries • Supported in part by GVU seed • Designing Human-Robot Collaborative Teams • Create, demonstrate and evaluate methods to design human-robot teams that collaborate effectively • Build a framework of affective robotic behavior to facilitate the collaboration • Will focus on the second goal (the corresponding paper will be presented at IEEE Conference on Systems, Man and Cybernetics, Washington, DC, Oct. 8 2003

3. Overview • Motivation and Related Research • Architectural Framework • Psychological Foundations • Integration into AuRA (Autonomous Robot Architecture) • Exploratory Experimental Study • Scenario • Study Design • Evaluation Methods

4. TAMEing??? • Of course, it’s an acronym! • TAME = traits, attitudes, moods, emotions • But there’s more to it… • “domesticating”: • Quality of interaction: ease and pleasantness • Safety • Bonding/attachment • In short, TAMEing = making robots suitable to live in our world • As situated and embodied companions, as opposed to lifeless machines

5. Topic and Research Questions • Build an Integrative Framework for Time-Varying Affective Robotic Behavior: Cognitive Perspective and Implications for Human-Robot Interaction • Can integration of various affective processes, such as moods, emotions, and attitudes help achieve synergy in generating affective behavior? • What are the implications for HRI? Can complex affective robotic behavior help lead to more natural communication between humans and robots? • Can the framework help make better predictions about human affective phenomena and potentially be a test-bed for cognitive/emotion psychologists? • Can adding affective behaviors help robots achieve certain tasks more efficiently?

6. Why Affective? • At least two reasons: • Because of us • people treat computers as social actors (Clifford Nass), even if they don’t realize it themselves • anecdotal evidence: military (!) personnel gets attached to simulated robots by the end of day’s training • Challenging – affective phenomena are often misunderstood • Because of them • It’s all about adaptation • affective phenomena are argued to have evolved to serve various adaptive purposes

7. Why Robotic? • That’s where the future is! • entertainment, edutainment, service robotics, elder-care, etc. • Dynamic and Uncertain Environments • where else is the need for fast-paced adaptation greater? • Continuous vs. Discrete • emotion and mood generation follows continuous paradigm – robotics as test-bed • Embodied Cognition • does our embodiment define our cognitive and emotive processes?

8. Related Work • Cynthia Breazeal: robotic creature Kismet • modeled after an infant; • capable of proto-social responses, providing an untrained user with natural and intuitive means of communication; • Juan Velasquez: emotion-based approach to robotics • extends the role of emotion from emotional expression for communication purposes to a determining factor in decision-making processes • Ron Arkin: Ethological and Emotional Basis for HRI • Emotions and drives for Sony entertainment robot Aibo • Affect-related work in animation and autonomous agents domains

9. General Approach • Interactionist approach: Combine a number of time-varying affective phenomena, such as personality traits, affect-based attitudes, moods and emotions in a unified framework, and explicitly define interactions between them and the robotic system

10. TAMEModule Affective State Disposition/Personality Process Model of Emotion Affect-based Attitudes (sentiment) Traits – FFM neuroticism extraversion openness agreeableness conscientiousness Mood Component Perceptual Input; Current State Behavior Coordination Motor Vector Robot Behavioral Assemblage Active Behaviors Behavioral Parameters Behavior 1 Perceptual Module Behavior … Behavior n TAME:Traits, Attitudes, Moods and Emotions Environment

11. Behavior-Based Robotic Paradigm • Robot’s control program consists of a collection of behaviors and coordination mechanisms; • Primitive behaviors have a set of defining parameters (e.g., obstacle avoidance sphere) and can be combined into assemblages, where each of the primitive behaviors is weighted; • Perceptual input causes transitions between behaviors, and the output of the behavior coordination potentially results in a motor action.

12. How TAME fits in • Composed of four interrelated components: Personality Traits, Attitudes, Moods, and Emotions • Emotions and moods constitute dynamically changing robot’s affective state • Traits and attitudes are more or less time-invariant, and define general dispositions • The module continuously (in parallel) scans the environment for relevant cues • Instead of directly defining behavioral transitions, the module rather modifies behavioral parameters, which affect currently active behaviors

13. Psychological Foundations • Each component serves a distinct adaptive function: • traits serve as an adaptation mechanism to specialized tasks and environments • emotions mobilize the organism to provide a fast response to significant environmental stimuli • moods bias behavior according to favorable/unfavorable environmental conditions • attitudes facilitate decision-making process by reducing decision space

14. Global/non-specific Traits Moods Instantaneous Life-time Attitudes Emotions Focused/specific Position in Time/Specificity Space

15. Personality Traits • Five-Factor Model (FFM) of Personality developed by McCrae and Costa serves as a basis for the trait component • Offers a comprehensive taxonomy, consistent over time, age and cultural differences • Personality traits, are mainly inherited or imprinted by early experience • Influence a wider range of behavior than emotions, as they are not limited to emotionally-charged situations

16. Dimensions of FFM • Neuroticism (N): contrasts adjustment or emotional stability with maladjustment or neuroticism; the general tendency to experience negative affects such as fear, sadness, etc. is the core of the N domain; • Extraversion (E): refers to liking people and preferring large groups and gatherings, being sociable, assertive, active and talkative;

17. Dimensions of FFM, cont. • Openness (O): the elements of O are active imagination, preference for variety, intellectual curiosity, and independence of judgment; • Agreeableness (A): a dimension of interpersonal tendencies, refers to being altruistic, sympathetic to others, cooperative and eager to help; • Conscientiousness (C): concerns the control of impulses; high scores mean purposeful, strong-willed, achievement – oriented individuals.

18. Emotions • Emotion is an organized reaction to an event that is relevant to the needs, goals, or survival of the organism (Watson) • Short in duration and noncyclical • Characterized by a high activation state and significant energy and bodily resources expenditure • Core set of emotions modeled are: joy, interest, surprise, fear, anger, sadness and disgust

19. Functions of Select Emotions • Interest: • Motivates exploration and learning; guarantees person’s engagement in the environment; serves as a mechanism of selective attention; • Joy/happiness: • Contributes to affiliative behavior and strengthens social bonds; has recuperative powers and serves as antidote to stress; • Anger: • Mobilizes and sustains energy at high levels; • Fear: • Motivates escape from dangerous situations; organizes and directs perceptual and cognitive processes, focusing attention on the source of threat

20. Moods • Mood is a continuous variable affective state, or “stream of affect” (Watson); • Represents low activation state and is less intense than emotion; • Expends less energy and bodily resources than emotion; • Two dimensions: positive affect and negative affect, which are fairly independent of each other • Correlated with FFM: e.g., Neuroticism is strongly correlated with negative affect, Extroversion -with positive; Conscientiousness is moderately correlated with positive affect; and Agreeableness is negatively correlated with negative affect

21. Affect-Based Attitudes • Attitude component forms attitudes towards particular objects or situations, and reduces decision state space by automatically rejecting outcomes connected to undesirable entities/events (e.g., dislike or hatred), or providing incentive for choosing those connected to desirable entities/events; • Functions of attitudes: • Adaptive (guides behavior towards desirable goals); • Knowledge (e.g., stereotypes and prejudices); • Expressive (expressing personalities and values); • Ego-defensive (protecting from self-threatening thoughts);

22. Integration with AuRA • MissionLab as a version of Autonomous Robot Architecture (Arkin, Balch) • Overall hybrid architecture is schema-based reactive system at a low-level combined with a high-level deliberative system • The reactive component is composed of primitive behaviors (schemas) grouped into behavioral assemblages; • Each individual primitive behavior produces a motor response based on relevant perceptual input, and behavior fusion is done through cooperation, by summing up vector responses from each of the active schemas, where the normalized weighted sum of vectors forms an overall motor output

23. Integration with AuRA, cont. • Each schema is weighted by a gain value, thus determining the relative importance of each primitive behavior • A finite-state automation defines the high-level plan of a robot’s mission, where each state corresponds to a behavioral assemblage, and perceptual inputs (“triggers”) cause transitions between the states

24. Integration with AuRA, cont. • Each TAME component is implemented as a set of primitive behaviors • These don’t output motor vectors, but rather change parameters for relevant motor schemas • Each component runs as a separate thread continuously throughout the execution (except for Traits, which are defined once per execution).

25. Example: Obstacle Avoidance • Obstacle avoidance is a primitive behavior, and the magnitude of the motor vector it outputs is defined as follows: • In case of trait influence, we would modify the parameters of obstacle gain and sphere of influence to obtain the vector magnitude where S is the default sphere of influence, R is the radius of the obstacle, G is the default avoidance gain, and d is the distance of robot to center of obstacle.

26. Trait Influence on Parameters • User defines a personality configuration • New behavioral parameters are calculated once at the beginning of execution based on user-defined traits • More than one trait can influence a parameter, and their combination produces an overall personality value affecting a particular parameter: • The new trait-based values modify the default ones:

27. Emotion Influence on Parameters • Emotions are dynamically generated throughout the execution • based on the presence and strength of environmental stimuli • Can have no, direct or inverse influence, and multiple emotions can be combined • Similarly to traits, emotions modify behavioral parameters:

28. Exploratory Experimental Study • Overall goal: to identify aspects of effective human-robot collaboration • In particular, specific affective phenomena to include into the framework • Robot as a companion • IRB-approved • Study: • Longitudinal study – 4 thirty-minute sessions to allow the subjects to bond with the robot • A new task for the participant to perform will be introduced at each session, and the last session will be cumulative.

29. Longitudinal Study Scenario • Robot as a pet and protector scenario • Aibo ERS 210A – Sony entertainment robot • 20 degrees of freedom • Expressive features: mouth, ears, tail, LCD display • Participants will be asked to interact with the robot over a number of short sessions, with the goal to assess the ease and pleasantness of interaction, as well as the extent to which they treat the robot as a companion (i.e., bond with it)

30. Study Design • Independent variable: presence of affect • No Affect vs. Affect Conditions • Affect condition: high on openness, agreeableness, and extraversion • Dependent variables: • Pleasantness of interaction • Amount of praise, petting, results of questionnaires • Ease of interaction • Time taken to make the dog perform a task; number of time succeeded • Level of bonding • The dog was given a nickname, total time of play…

31. Study Design, cont. • Hypotheses: • Null hypothesis: there will be no difference in participants’ attitude towards the robot • Alternative: Pleasantness and ease of interaction will be greater in Affect condition than in No Affect condition; • Bonding will be the greater in Affect condition.

32. Tasks • Follow the ball; kick the ball • Participant asks the dog to follow a ball • And/or to kick it when close • Come here • Participant asks the dog to move towards him/her and stop when close • Follow me • The dog follows the person • “Sick ‘em!” • The dog will move to intercept the intruder (Amigobot)

33. Evaluation Methods • Introspection: • Negative/positive emotionality questionnaire • Goldberg’s Unipolar Big-Five Markers Questionnaire • Post-study questionnaire • Observation: • Average distance to the robot • Number of times the robot was petted/touched • Ratio of praise to scolding to neutral utterances • Analysis of interactive behaviors (e.g., talking to the robot, petting it, etc.)

34. What Next? • Perform the study • Extract the information to inform the framework • Explore time-varying aspects of affective phenomena • Extend affect-behavior mapping • Explore the interactions between affective phenomena

35. Rhetorical Question: Do we really need TAME robots? Rhetorical Answer: Just think of the alternative! Thank you!