HPM in HMI Design Part II - Modelling
Overview • Part I - Introduction – Applied Cognitive Modelling – From Control Theory to Cognitive Functions • Part II - Modelling – HPM Engineering Life Cycle – ACT-R 6.0 for runaways – Advanced Modelling Tools TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 2
Human Performance Model Engineering Life Cycle
Plausibility Problem Simulation Formulation results Proof of Verification of concept Results Conceptual modelling Experimentation Conceptual Computer Model Model Mathematical Implementation modelling Formal Proof of Model formalisation Program verification (Fig. adopted from Lugner & Bub 1990) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 4
Plausibility Problem Simulation Formulation results Proof of Verification of concept Results Conceptual modelling Experimentation Conceptual Computer Model Model Mathematical Implementation modelling Formal Proof of Model formalisation Program verification Step 1 – Problem Formulation What do we want to achieve with the HPM? How much effort can we afford? What confidence is necessary for the models predictions? TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 5
Plausibility Problem Simulation Formulation results Proof of Verification of concept Results Conceptual modelling Experimentation Conceptual Computer Model Model Mathematical Implementation modelling Formal Proof of Model formalisation Program verification Step 2 – Conceptual Model What Level of Detail is necessary? Which HPM method is appropriate? Conduct a Cognitive Task Analysis! • Select appropriate CTA Method (see Schraagen et al. 2000) • Identify goals, knowledge structures and information processing strategies, heuristics, sources of control, ... Which cognitive theories and experimental results can we build upon? Which Architecture / Integrated Theory of Cognition is capable to ? Which additional assumptions and/or experimental Data is needed? How can we test our modelling assumptions? TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 6
Zeit (sec) Einheiten System Analyse Activities/ World (theory) Processes 10 5 days 10 4 hours Task Task analysis Subtasks Bounded Rationality 10 3 10 min 10 2 min Subtask Unit Task Analysis Unit Tasks 10 1 10 sec Unit task Cognitive task analysis Activities 10 0 1 sec Activity Embodied cognition Microstrategies Cognitive Band Computational models 10 -1 100 ms Microstrategy Elements of embodied cognition 10 -2 10 ms Elements Architectural Parameters Biological Band 10 -3 1 ms Parameters (Gray & Boehm-Davis, 2000) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 7
Fokus Informationsverarbeitung subjective value formation Information, Goals, Preferences Task order Behaviour Mental Information Processing Cognitive Resources, Attention Psychological mechanisms Arrousal, Stress, Fatigue Physiologic Functions Physical Capabilities, Challenges Anatomic Properties (Fig. adapted from Rasmussen, 1986) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 8
Theory Driven Human Performance Modelling • HPM simulate processes Processes that generate observable behaviour according to describe generate some cognitive theory • Unfortunately cognitive explain Theories Behaviour theories were most often simulate not developed with the implement generate goal to support computation HPM (Cooper 1999) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 9
Theory Driven Human Performance Modelling Processes describe generate • HPM simulate processes that generate observable explain Theories Behaviour behaviour according to some cognitive theory simulate implement generate • Unfortunately cognitive theories were most often HPM not developed with the goal to support computation (Cooper 1999) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 10
Conceptual Model Rational Analysis (Anderson 1998) Goal Structures Knowledge Representation (Facts & Procedures) procedural (non-concious but observable) declarative (concious and explicable) Volitional Control of Behaviour Internal / External Control Conflict Resolution Predefined concurrent pathes of execution Learning Procedural: Subsymbolic Utility / Production Compilation Declarative: Subsymbolic Activation / Creation of new TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 11 Facts
Plausibility Problem Simulation Formulation results Proof of Verification of concept Results Conceptual modelling Experimentation Conceptual Computer Model Model Mathematical Implementation modelling Formal Proof of Model formalisation Program verification Step 3 – Formal Model Translate concept on primitives of selected Architecture Implement Control Flow Extend Architecture if primitives are not sufficient? TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 12
A very short introduction to ACT-R
Intentional Module Deklarative Memory ACT-R 6.0 (not identified) (Temporal/Hippocampus) (Anderson et al. 2004) Goal Buffer Retrieval Buffer (DLPFC) (VLPFC) • Production System (Basal Ganglia) 1. Evaluation (Striatum) • Unified Cognitive Theory Productions • Buffers „hide“ complexity 2. Selection (Pallidum) of computation in modules and provide a 3. Execution (Thalamus) common API • Still Research: Mapping Visual Buffer Manual Buffer of Modules and Functions (Parietal) (Motor) to Brain Areas Visual Module Motor Module (Occipital/Parietal) (Motor/Cerebellum) External Task Environment (Abb. nach Taatgen 2004) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 14
Declarative Memory Properties Symbolic Level Associative Memory organized as a Semantic Net of CHUNKs with infinite Capacity (Anderson 1974, Anderson & Lebiere 1993) Subsymbolic Level • Activation based Retrieval Retrieval Time = f(Activation of Memoryelements) • Activation Decay Seldomly used Memory Elements are harder to retrieve than recently retrieved ones • Activation Spreading Usage of Memory Elements in Buffers rises activation of element and related chunks TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 15
Declarative Memory Syntax CHUNK: typed data structure that has a unique name and may contain named references to other CHUNKS or terminal SYMBOLs like numbers. CHUNK-TYPE: Definition of CHUNK structure SLOT: Named Elements of a CHUNK (chunk-type NAME-OF-TYPE NAME-OF-SLOT-1 NAME-OF-SLOT-2 … ) (add-dm ( NAME-OF-CHUNK-1 isa NAME-OF-TYPE NAME-OF-SLOT-1 VALUE-OF-SLOT-1 NAME-OF-SLOT-2 VALUE-OF-SLOT-2 … ) ( NAME-OF-CHUNK-2 isa … ) ) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 16
Declarative Memory Example (chunk-type number) (chunk-type addition-fact addend1 addend2 sum) (add-dm (seven isa number) (two isa number) (nine isa number) (fact-7+2=9 isa addition-fact addend1 seven addend2 two sum nine) ) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 17
Production Rules Mental Information Processing is coded in form of Productions with a highly restricted set of information processing primitives IF Condition THEN Action Conditions: State and Content of Buffers Actions: Retrieval from Memory, Attention to Visual System, Issue Command to Motor System Modification of Retrieval/Goal Buffer Content Store to Memory (via clear Buffer) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 18
Intentional Module Declarative Memory (not identified) (Temporal/Hippocampus) Goal Buffer Retrieval Buffer (DLPFC) (VLPFC) (Basal Ganglia) 1. Evaluation (Striatum) Productions 2. Selection (Pallidum) 3. Execution (Thalamus) Visual Buffer Manual Buffer (Parietal) (Motor) Visual Module Motor Module (Occipital/Parietal) (Motor/Cerebellum) External Task Environment (Abb. nach Taatgen 2004) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 19
Production Rule Syntax ( P NAME-OF-PRODUCTION =BUFFER-1> NAME-OF-SLOT-1 ( Condition | Variable ) NAME-OF-SLOT-2 ( Condition | Variable ) =BUFFER-2> NAME-OF-SLOT-3 Condition … ==> =BUFFER-1> NAME-OF-SLOT-1 ( Symbol | Variable ) NAME-OF-SLOT-2 ( Symbol | Variable ) +BUFFER-2> NAME-OF-SLOT-3 ( Symbol | Variable ) ) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 20
Slot Content Primitives Condition - Slot contains specified Symbol - Slot contains any Symbol (value bound to variable) - two or more slots of any number of buffers contain the same symbol Action - set content to value of symbol - set content to bound variable TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 21
Evaluate – Select – Execute Cycle • All Productions are evaluated every 50 ms! • Out of the set of matching productions (conflict set), one candidate is elected to be executed. • Conflict Resolution by comparing learned utility of production rule • This kind of modelling is fun for 10 to 50 production rules • more rules are hard to oversee and even harder to maintain • In more complex domains: Lots of 'Hand Weaving' from Conceptual Model to Formal Computer Model! • Abstraction Layer provides no means for part-model reuse (but of course one can program some lisp macros ;-) TU Dresden, 03/09/08 ICCL Summer School 2008, Urbas Slide 22
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