(How) Can Appraisal Theory be Formalized at a Meta-level?

1. (How) Can Appraisal Theory be Formalized at a Meta-level? Joost Broekens, Doug DeGroot LIACS, Leiden University

2. Why formalize appraisal structure at high level? • Appraisal theory development. • Comparison, refinement, convergence • Architectural basis for computational models • Development and debugging.

3. Emotions in Agents • What is an emotion? • Heuristic relating events to goals, needs, desires, beliefs of an agent (cognitive definition). • Communication medium. • Related to homeostasis and hormonal state • Why use an emotion in agents and robots? • heuristic aspect (efficient evaluation), communicative aspect. • Which agents might need emotions? • Games, HCI, HRI, Virtual-Reality, Decision-making and planning. • Computational models of emotion, in general, are based on Cognitive Appraisal Theory.

4. Structural Theories (what), Process Theories (how) • Structural Theory: structural relation between: • Environment of agent (perception) • Appraisal processes that interpret the environment in terms of values on appraisal dimensions (appraisal) • Mediating processes that relate appraisal dimension values to emotions (mediation) • Processes are black-boxes. • Declarative semantics • Process Theory: • Detailed cognitive operations and mechanisms involved in processes and their interaction as described by structural theory of appraisal. • Procedural (cognitive) semantics

5. Computational models of Emotions • Structural Theory + assumptions from AI = computational model (Gratch and Marsella, 2004). • This poses a problem (Gratch and Marsella, 2004) • Structural Appraisal Theory: abstract. • Computational model: algorithmic, detailed. • What if the model does something unexpected? Structural Theory Computational Model Gap AI Assumptions

6. Structural Theory Formal Description Computational Model Assume less Smaller Gap Situation :-) ? What’s wrong? • The Computational Model or the Theory (or the observer)? Structural Theory Computational Model AI Assumptions Gap Situation

7. Problem: How to Debug Your Computational Model? • Debugging is a problem: • Large gap between theory and computational model. • Highly complex agent designs complicate debugging. • Understanding emotions is not something computer scientist are trained, in contrast it’s the appraisal theorist’s job.

8. Benefits of Such Formalisms • Appraisal Theory • Comparison, Integration, Convergence (Wherle and Scherer, 2001) • Precise and structured theory revision • Process of Formalization helps theory development and refinement. • Formal annotation of experimental results. • Computational models • Formal architecture of appraisal. • Evaluation of computational model in relation to the theory • Structured storage of annotated experimental results (human/agent) • Compare computational models. • Feedback to theory and human-subject based experimental results

9. Requirements for a Formalism for the Structure of Appraisal • How many, which processes exist (perception, appraisal, mediation) • When and how are these activated (threshold, continuous?) • How much time needed to evaluate? • What kind of information needed for these processes? • How many and which appraisal dimensions, emotional response components? • How do appraisal dimension values relate to emotional response components? • See also (Reisenzein, 2001).

10. External World (W) Mental Objects (O) Appraisal Dimension Values (V) Emotion Component Intensities(I) P A M Overview of the Formalism (1/4): Perception • W = observable objects and events in the environment of the agent • P = the set of all perception processes available to the agent. pi:WnVnInOni. Is a perception process translating the world into mental objects (O) in the context of a current emotion (I) and appraisal state (V). • O = set of all mental objects currently perceived by the agent with

11. External World (W) Mental Objects (O) Appraisal Dimension Values (V) Emotion Component Intensities(I) P A M Overview of the Formalism (2/4): Appraisal • A = the set of appraisal processes. ai:OnInVin , ai is an appraisal process, mapping mental objects (O) to possible appraisal dimension values (V) in the context of the current emotion (I). • D = set of appraisal dimensions defined by the theory. • V = set of current appraisal dimension values VOnD[-1,1]

12. External World (W) Mental Objects (O) Appraisal Dimension Values (V) Emotion Component Intensities(I) P A M Overview of the Formalism (3/4): Mediation • E = set of possible emotional response components • I = set of emotional response component intensities I=IE[0,1] • M = set of mediating processes. mj:VnIj is a mediating process relating appraisal dimension values (V) to emotional component intensities (I)

13. External World (W) Mental Objects (O) Appraisal Dimension Values (V) Emotion Component Intensities(I) P A M Overview of the Formalism (4/4): Process dependencies • PP = set of all processes (P, A and M) • LT= set of process dependency types. • G = set of guards • L = set of process dependencies. L = PPxPPxGxLT • (x)(y) processing in qxis influenced iff ((py,qx,g,n)L  g=true  p,qPP  gG  nN)If a dependency exists between a process p and q and the guard g of that link is true, processing in q is influenced in a way denoted by the type n

14. Formalization of structure • Appraisal theory development. • Architectural basis for computational models

15. Application 1: Integration of two Appraisal Theories. • Integration based on: • Scherer’s Stimulus Evaluation Checks (SEC) (Scherer, 2001) • Smith and Kirby’s Appraisal Detector Model (ADM) (Smith and Kirby, 2000) • SEC: multiple appraisal processes (stimulus checks) • Appraisal Processes activate in four* consecutive steps: Relevance detection, Implication assessment, Coping potential, Norm/self compatibility. • Processes exist at three perception levels: sensory-motor, schematic, conceptual. • Current result of appraisal processes stored in appraisal registers. * Here we only use the first three.

16. Application 1: Integration • ADM: • Appraisal detectors integrate appraisal information coming from different perception levels (levels equivalent to those defined in SEC, i.e., sensory-motor, schematic, conceptual) • Appraisal detectors produce emotional response. • Feedback from emotional response to processing, specifically conceptual (reasoning) and schematic (associative learning) levels. • Integration basics: common architectural concepts • Separation of appraisal in three levels of information processing. • Appraisal registers/detectors

17. Suddenness Familiarity Predictability Intrinsic pleasantness Goal/Need relevance Novelty Schematic Relevance detector Stimulus perception Conceptual Causal attribution Agency Outcome probability Expectation discrepancy Goal/Need conduciveness Urgency Intentional attribution Implication detector Control Power Adjustment Coping pot. detector Application 1:Integration

18. Suddenness Familiarity Predictability Intrinsic pleasantness Goal/Need relevance Novelty Schematic Relevance detector Stimulus perception Conceptual Causal attribution Agency Outcome probability Expectation discrepancy Goal/Need conduciveness Urgency Intentional attribution Implication detector Control Power Adjustment Coping pot. detector Application 1:Integration

19. Suddenness Familiarity Predictability Intrinsic pleasantness Goal/Need relevance Novelty Schematic Relevance detector Stimulus perception Conceptual Causal attribution Agency Outcome probability Expectation discrepancy Goal/Need conduciveness Urgency Intentional attribution Implication detector Control Power Adjustment Coping pot. detector Application 1:Integration

20. Suddenness Familiarity Predictability Intrinsic pleasantness Goal/Need relevance Novelty Schematic Relevance detector Stimulus perception Conceptual Causal attribution Agency Outcome probability Expectation discrepancy Goal/Need conduciveness Urgency Intentional attribution Implication detector Control Power Adjustment Coping pot. detector Application 1:Integration

21. Suddenness Familiarity Predictability Intrinsic pleasantness Goal/Need relevance Novelty Schematic Relevance detector Stimulus perception Conceptual Causal attribution Agency Outcome probability Expectation discrepancy Goal/Need conduciveness Urgency Intentional attribution Implication detector Control Power Adjustment Coping pot. detector Application 1:Integration

22. Suddenness Familiarity Predictability Intrinsic pleasantness Goal/Need relevance Novelty Schematic Relevance detector Stimulus perception Conceptual Causal attribution Agency Outcome probability Expectation discrepancy Goal/Need conduciveness Urgency Intentional attribution Implication detector Control Power Adjustment Coping pot. detector Application 1:Integration

23. Application 2: Formal Description of a Computational Model • Formal description: • Based on simplified version of integrated model (SSK) • Used to define the architecture of appraisal (i.e., appraisal steps, appraisal detectors, levels of perception, appraisal dimensions) • Used to evaluate behavior of resulting computational model of emotions. • Test environment: PacMan • Appraisal of events in PacMan’s environment is simulated. • Architecture and appraisal dimensions used based on simplified SSK model

24. Application 2: Comp. Model

25. Formal description helped to verify model’s behavior. • No activation of relevance detection… • Due to bipolar variable: conductiveness. • Summing negatively conductive and positively conductive events results in no conductivity activation not plausible. • Separate conductiveness in pos and neg. • Relevance detection active and activation of implication checks at right moments.

26. Some Conclusions • Formal description facilitated development of computational model. • Clear definition of architecture of appraisal processes • Formalism facilitated integration of theories. • Open: • How to formally encode experiments and experimental results, comparing experimental results, etc. • What is the relation between BDI-based formalism and Meta-level formalisms.

27. Questions? Referred literature: Reisenzein, Rainer. Appraisal Processes Conceptualized from a Schema-Theoretic Perspective: Contributions to a Process Analysis of Emotions. 2001. Smith, Craig A., Kirby, Leslie D. Consequences require antecedents: Toward a process model of emotion elicitation. 2000. Wherle, Thomas and Scherer, Klaus R. Towards Computational Modeling of Appraisal Theories. 2001. Scherer, Klaus R. Appraisal Considered as a Process of Multilevel Sequential Checking. 2001. Gratch, Jonathan and Marsella, Stacy. A domain independent framework for modeling emotion. 2004 . Broekens and DeGroot,. Formal Models of Emotion: Theory, Specification and Computational Model. 2004 Link types, guards, data constraints and dependencies: LT={ activation} G={ true, guard1, guard2, guard3} with: guard1=((x,y,z) x,y,zV  x=(o,d,i)  y=(o,d',j)  z=(o,d'',k)  (i+j+k)/3>.15  d=novelty_dim  d'=intrinsic_dim  d''=relevance_dim) guard2=((x,y) x,yV  x=(o,d,i)  y=(o,d',j)  (i+j)/2>.25  d=conductiveness_dim  d'=urgency_dim) guard3=((x,y) x,yV  x=(d,i)  y=(d',j)  i*j>0  d=control_dim  d'=power_dim) H={ c1, c2} with: c1= ((x)xV  x=(y,d,i,t)  i>0) if ((y)yO  y=(c,j,t')  j>0  t=t'), and c2= ((z)zI  z=(e,i',t'')  i'>0) if ((x')x'V x'=(y',d,j',t''')  j'>0  t''=t''')}. L={ (stimulus_perception, suddenness, true, activation), (stimulus_perception, intrinsic_pleasantness, true, activation), (stimulus_perception, relevance, true, activation), (stimulus_perception, conductiveness, true, activation), (stimulus_perception, urgency, true, activation), (stimulus_perception, power, true, activation), (schematic, familiarity, true, activation), (schematic, relevance, true, activation), (schematic, conductiveness, true, activation), (schematic, urgency, true, activation), (schematic, control, true, activation), (suddenness, novelty, true, activation), (familiarity, novelty, true, activation), (novelty, relevance__detector, true, activation), (intrinsic_pleasantness, relevance_detector, true, activation), (relevance, relevance_detector, true, activation), (relevance_detector, conductiveness, guard1, activation), (relevance_detector, urgency, guard1, activation), (conductiveness, implication_detector, true, activation), (urgency, implication_detector, true, activation), (implication_detector, control, guard2, activation), (implication_detector, power, guard2, activation), (control, coping_potential_detector, guard3, activation), (power, coping_potential_detector, guard3, activation)} Perception appraisal and mediating processes: P={ stimulus_perception, schematic} A={ suddenness, familiarity, novelty, intrinsic_pleasantness, relevance, conductiveness, urgency, control, power} M={ relevance_detector, implication_detector, coping_potential_detector} Mental object types, mental objects, appraisal dimensions and emotion components: OT={ belief} PO={ (see_ghost, belief), (lost_ghost, belief), (eaten_by_ghost, belief), (see_edible_ghost, belief), (lost_edible_ghost, belief), (eaten_ghost, belief), (see_power, belief), (eaten_power, belief), (see_dot, belief), (eaten_dot, belief), (see_fruit, belief), (lost_fruit, belief), (eaten_fruit, belief)} D={ novelty_dim, intrinsic_pleasantness_dim, conductiveness_dim, urgency_dim, control_dim, power_dim} E={}