A Bisimulation-Based Approach to the Analysis of Human-Computer - PowerPoint PPT Presentation

A Bisimulation-Based Approach to the Analysis of Human-Computer Interaction S´ ebastien Comb´ efis Charles Pecheur Universit´ e catholique de Louvain (UCLouvain) Belgium July 16, 2009 [EICS’09, Pittsburgh, PA, USA]

Complex Systems With Automation and Human-Interaction ◮ Accidents: bad system design, bad operator, wrong interaction S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 2

Human-Computer Interaction Different Components system mental model system model user user manual, interface training S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 3

Human-Computer Interaction Different Components system mental model system I n t e model r a c t i o n user user manual, interface training S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 3

Human-Computer Interaction Different Components system mental model system I n t e model r a c t i o n Interacts user user manual, interface training S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 3

Human-Computer Interaction Different Components system mental model Abstracts system model user user manual, interface training S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 3

Human-Computer Interaction Different Components system mental model system model Induces user user manual, interface training S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 3

Human-Computer Interaction Different Components system mental model system model user user manual, interface training Objective: Generate an abstraction of a given system model Motivation: Build training material to enforce a good mental model S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 3

Human-Computer Interaction Different Components system mental model system model user user manual, interface training S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 3

Human-Computer Interaction Different Components system mental model system model user user manual, interface training S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 3

Outline 1 Introduction 2 Modelling Human-Computer Interaction 3 Generating Full-Control Mental Model 4 Conclusion S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 4

Models of the System The Big Picture . . . Training Social Learning Manual Mental Model Tasks Operational Model Environment Full-Control Model derives System Model influences S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 5

Models of the System The Big Picture . . . Training Social Learning Manual Mental Model Tasks Operational Model Environment Full-Control Model ALL BEHAVIOUR derives System Model influences S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 5

Models of the System The Big Picture . . . Training Social Learning Manual Mental Model Tasks Operational Model PARTIAL BEHAVIOUR Environment Full-Control Model derives System Model influences S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 5

Models of the System The Big Picture . . . Training Social Learning Manual Mental Model CHANGES Tasks Operational Model Environment Full-Control Model derives System Model influences S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 5

Labelled Transition Systems The Vehicle Transmission System Example ◮ Semi-automatic gearbox (Degani, 2007) GEAR LEVER push-up pull-down S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 6

Labelled Transition Systems The Vehicle Transmission System Example ◮ System modelled as a Labelled Transition System (LTS) high-1 high-2 high-3 state push-up pull-down transition medium-1 medium-2 up with action down low-1 low-2 low-3 LTS executions yield traces Action-Based Interface: command , observation , τ S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 6

Vehicle Transmission System A Mental Model ◮ The user sees the system as a three-state system high push-up pull-down medium up down low S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 7

Vehicle Transmission System A Mental Model ◮ The user sees the system as a three-state system high push-up pull-down medium up down low S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 7

Capturing Possible Interactions Synchronous Parallel Composition System Model Mental Model high-1 high-2 high-3 high medium-1 medium-2 medium low-1 low-2 low-3 low up push-up pull-down down S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 7

Capturing Possible Interactions Synchronous Parallel Composition System Model Mental Model high-1 high-2 high-3 high medium-1 medium-2 medium low-1 low-2 low-3 low up push-up pull-down down S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 7

Capturing Possible Interactions Synchronous Parallel Composition System Model Mental Model high-1 high-2 high-3 high medium-1 medium-2 medium low-1 low-2 low-3 low up push-up pull-down down S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 7

Capturing Possible Interactions Synchronous Parallel Composition System Model Mental Model high-1 high-2 high-3 high medium-1 medium-2 medium low-1 low-2 low-3 low up push-up pull-down down S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 7

Full-Control Mental Model Capturing All Behaviours of the System Definition (Full-control mental model) A mental model allows full-control of a system iff for all sequences of observable actions σ such that σ σ = = ⇒ s M and s 0 U → s U : s 0 M − − A c ( s M ) = A c ( s U ) A o ( s M ) ⊆ A o ( s U ) ∧ ◮ Intuition: For each state in the synchronous parallel composition: Exactly same commands on system and mental models At least all observations of system model on mental model S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 8

Outline 1 Introduction 2 Modelling Human-Computer Interaction 3 Generating Full-Control Mental Model 4 Conclusion S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 9

Mental Model Generation Full-Control Equivalence Generating a minimal full-control mental model for a system Defining an equivalence relation ≈ fc on system’s states Merging equivalent states together to get a reduced model S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 10

Mental Model Generation Full-Control Equivalence Generating a minimal full-control mental model for a system Defining an equivalence relation ≈ fc on system’s states Merging equivalent states together to get a reduced model s ≈ fc t if and only if ◮ α a command α α α ⇒ t ′ : s ′ ≈ fc t ′ ⇒ s ′ ∃ t ∀ s = = = = s s’ ≈ fc ≈ fc α t t’ S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 10

Mental Model Generation Full-Control Equivalence Generating a minimal full-control mental model for a system Defining an equivalence relation ≈ fc on system’s states Merging equivalent states together to get a reduced model s ≈ fc t if and only if ◮ α a command β α α ⇒ t ′ : s ′ ≈ fc t ′ ⇒ s ′ ∃ t ∀ s = = = = s s’ ◮ β an observation ≈ fc β β ⇒ s ′ : ∃ t ⇒ t ′ ⇒ s ′ ≈ fc t ′ = = = = ∀ s t S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 10

Mental Model Generation Full-Control Equivalence Generating a minimal full-control mental model for a system Defining an equivalence relation ≈ fc on system’s states Merging equivalent states together to get a reduced model s ≈ fc t if and only if ◮ α a command β α α ⇒ t ′ : s ′ ≈ fc t ′ ⇒ s ′ ∃ t ∀ s = = = = s s’ ◮ β an observation ≈ fc ≈ fc β β ⇒ s ′ : ∃ t ⇒ t ′ ⇒ s ′ ≈ fc t ′ = = = = ∀ s β t t’ S. Comb´ efis, C. Pecheur (UCLouvain) – A Bisimulation-Based Approach to the Analysis of HCI 10