How Can Appraisal Theory be Formalized at a

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

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

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.

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

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 Gap Computational Model AI Assumptions

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

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.

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 theory – Structured storage of annotated experimental results (human/agent) • Compare computational models. • Feedback to theory and human-subject based experimental results

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).

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 External World (W) P Mental Objects (O) A Appraisal Dimension Values (V) M Emotion Component Intensities(I)

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 theory. • V = set of current appraisal dimension values V On D [-1, 1] External World (W) P Mental Objects (O) A Appraisal Dimension Values (V) M Emotion Component Intensities(I)

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) External World (W) P Mental Objects (O) A Appraisal Dimension Values (V) M Emotion Component Intensities(I)

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 = PPx. Gx. LT ( x)( y) processing in qx is 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 External World (W) P Mental Objects (O) A Appraisal Dimension Values (V) M Emotion Component Intensities(I)

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

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.

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

Application 1: Integration 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 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 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 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 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 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 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: Pac. Man – Appraisal of events in Pac. Man’s environment is simulated. – Architecture and appraisal dimensions used based on simplified SSK model

Application 2: Comp. Model

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.

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.

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 De. Groot, . Formal Models of Emotion: Theory, Specification and Computational Model. 2004 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={} Link types, guards, data constraints and dependencies: LT={ activation} G={ true, guard 1, guard 2, guard 3} with: guard 1=(( 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) guard 2=(( x, y) x, y V x=(o, d, i) y=(o, d', j) (i+j)/2>. 25 d=conductiveness_dim d'=urgency_dim) guard 3=(( x, y) x, y V x=(d, i) y=(d', j) i*j>0 d=control_dim d'=power_dim) H={ c 1, c 2} with: c 1= (( x)x V x=(y, d, i, t) i>0) if (( y)y O y=(c, j, t') j>0 t=t'), and c 2= (( 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_detector, conductiveness, guard 1, activation), (relevance_detector, urgency, guard 1, activation), (conductiveness, implication_detector, true, activation), (urgency, implication_detector, true, activation), (implication_detector, control, guard 2, activation), (implication_detector, power, guard 2, activation), (control, coping_potential_detector, guard 3, activation), (power, coping_potential_detector, guard 3, activation)}