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Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 70
1 The topic2 Decision support systems3 Modeling
3.3 Advanced modeling
Outline
Compositional modeling: requirements Conceptual modeling: Why? How? Qualitative modeling: Why? Limitations? Automated model composition
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 71 71
Ecological Modeling and Decision Support Systems
Requirements
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 72
Model Structure (Townsend et al. 08)
Adult vultures in year t, Nt
SurvivalMaturation
and survival
Rate at which carcasses are
eaten, F
Probability of a carcass
containing diclofenac, C
Effect of diclofenac
Baseline survival, S
Rate at which carcasses are
eaten, F
Probability of a carcass
containing diclofenac, C
Effect of diclofenac
Baseline survival, S
Adult vultures in year t-1, Nt-1
Vulture births in year t-5
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 73
Re-arranged Structure of a Model of Vulture Population
Adult vultures in year t, Nt
Survival Maturation and survival
Adult vultures in year t-1, Nt-1
Vulture births in year t-5
Baseline survival, S
Probability of carcasses with diclofenac, C
Effect of diclofenac
Rate at which carcasses are
eaten, F
Why re-arranged? Reuse of model elements
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 74
Requirements
Compositional modeling– Complex model: aggregation of elementary model fragments– Requires conceptual modeling
Conceptual modeling– Represent objects, relationships, interactions explicitly
Qualitative modeling– Models capturing partial knowledge and information
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 75
1 The topic2 Decision support systems3 Modeling
3.3 Advanced modeling3.3.1 Conceptual modeling
Outline
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 76 76
Ecological Modeling and Decision Support Systems
Processes - Motivating Examples
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 77
Process-oriented Modeling - Part 1
Identify and model elementary, independentphenomena/interactions: “processes”
Populationsize
Reproduction
Death Immigration
Emigration
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 78
Process-oriented Modeling – Part 2
Identify preconditions for the process to happen– objects– object relations– quantity conditions
DiclCarcassesProb.: C>0
VulturePopN>0
SameLocation(VulturePop, DiclCarsasses)
DiclPoisoning
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 79
Process-oriented Modeling – Part 2 Cont’d
Identify preconditions for the process to happen– objects– object relations– quantity conditions
Resourcesamount>0
Populationdensity > d0
Accessible(Population, Resources)
Reproduction
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 80
Process-oriented Modeling – Part 3
DiclCarcasses
Vulture Pop
DiclCarcassesProb.: C>0
VulturePopN>0
SameLocation(VulturePop, DiclCarsasses)
DiclPoisoning
Identify and describe impact on objects/relations
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 81
Process-oriented Modeling – Part 3 Cont’d
Resources
Population
Resourcesamount>0
Populationdensity > d0
Accessible(Population, Resources)
Reproduction
Identify and describe impact on objects/relations
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 82
Process-oriented Modeling – Part 4
Describe effects on quantities
Resources
Population
Resourcesamount>0
Populationdensity > d0
Accessible(Population, Resources)
Reproduction
“ dN/dt = r·N ”?
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 83 83
Ecological Modeling and Decision Support Systems
Processes – More Formally
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 84
Process-Oriented Modeling
Model Fragment (Process) Conditions Structure (objects,
object relations) Quantities
Effects Structure Quantities
STRUCT-CONDS QUANT-CONDS
STRUCT-EFFECTS QUANT-EFFECTS
„Model“ in the„classical“ sense
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 85
Formal Basis for Reasoning about Models
Process: a logical formula deduction consistency check model composition model-based diagnosis model-based therapy …
STRUCT-CONDS QUANT-CONDS
STRUCT-EFFECTS QUANT-EFFECTS
Conceptual layer explanation education
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 86 86
Ecological Modeling and Decision Support Systems
More Examples and Demonstration
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 87
Example: Chloramin Reactions
Water treatment: protocol of knowledge acquisition from experts
Preconditions– Structural
(substances)– Quantity
Effects– Structural
(new substances)– Quantity
CHLORAMINE REACTION
NH4+ + HClO NH2Cl + H2O + H+ \monochloramines (1)
NH2Cl + HClO NHCl2 + H2O \dichloramines (2)
NHCl2 + HClO NCl3 + H2O \trichloramines (3)
The pH determines the stability of chloramine compounds. So in excess chlorine concentration,
it’s possible to say that monochloramine stability go down, and it decomposed to:
2NH2Cl + HClO N2 + 3HCl + H2O (4)
If the pH is favorable to dichloramines existence, it is decomposed as:
NH2Cl N2 + 2HCl + Cl2 (5)
Cl2 + H2O HClO + HCl (6)
If the pH is favorable to dichloramines and monochloramines existence, then (4) will be the
predominant reaction. So the water with this conditions won’t have trichloramine (NCl3), because
they will be reduced to dichloramine form, as:
NCl3 + H2O NHCl2 + HClO (7)
Finally, to simplifying the reaction it can be said that amonium is totally destroyed by chlorine as:
2NH3 + 3Cl2 6HCl + N2 (8)
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 88
Demonstration: SIMGEN for Tutoring
Runs a simulation answers queries about the simulation
- „WHAT happens?“: values, active processes about the domain theory
- „WHY does it happen?“: preconditions Example: different cups containing a liquid
under different conditions
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 89 89
Ecological Modeling and Decision Support Systems
Requirement: Context Independence
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 90
Context-independent Models
Compositional modeling re-usable model fragments re-usable in different contexts context-independent model fragments
refer to local variables only attributes of involved objects state all preconditions Otherwise: applied in wrong context specify effect locally “dN/dt = r·N” ???
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 91
Effects Cannot be Stated by Derivatives
dN/dt = r*N
Populationsize
Reproduction
Death Immigration
Emigration
?Solution ch. 2.3.3
Model-Based Systems & Qualitative ReasoningGroup of the Technical University of Munich WS 11/12 EMDS 3 92
Modeling Assumptions
Context-independent models In the ideal sense: impossible Complete preconditions? Unstated negative preconditions: “… and X must not be present”
Resourcesamount>0
Populationdensity > d0
Accessible(Population, Resources)
ReproductionResources
Population