1 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Model Building Experiences using Garp3: Problems, Patterns and Debugging Jochem Liem, Floris E. Linnebank & Bert Bredeweg Human-Computer Studies University of Amsterdam TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AA

2 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Motivation: Usability to Formalization Bottleneck Availability of usable QR tools has led to: – More domain experts formalizing their conceptual knowledge – The creation of more complex models Usability is no longer an issue However, knowledge formalization is the new bottleneck Modelers encounter similar representational issues, and reinvent solutions This paper categorizes representation issues and their solutions.

3 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Trained Groups in QR Modelling PhD-level researchers (NaturNet-Redime) – 2,5 year working with Garp3 – Trainings each half year – Support using Skype/Flashmeeting BSc. Students (Future Planet Studies) – 4 weeks: Concept maps, Ontologies – 4 week: QR modelling (Carbon Cycle) PhD-students (School for Information and Knowledge Systems) – 1 hour lecture + 2 hour practical: Tree & Shade model

4 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Entities or Quantities? Alternative representations: – Algae entity with Biomass quantity – Algea concentration quantity Create a new entity when properties of this entity are important. E.g. photosynthesis quantity of the algae Model by Elena Nakova, Yordan Uzunov

5 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Configuration direction & naming Model by Richard Noble, Floris E. Linnebank & Bert Bredeweg Prefer active voice over passive voice Shorter configuration names Improves texts based on QR models

6 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Relation reification Configuration direction is arbitrary Long configuration name Where to model speed of symbiosis process? Model by Paulo Salles & Bert Bredeweg

7 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Influences & Proportionalities Q1[+,-] Q2[+,?] I+ Q1[+,-] Q2[+,?] I- Q1[-,-] Q2[+,?] I+ Q1[-,0] Q2[+,?] I-

8 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Causal Interactions Q1[+,-] Q2[+,?] I+ Q1[+,-] Q2[+,?] I- Q1[-,-] Q2[+,?] I+ Q1[-,0] Q2[+,?] I- Q3[-,-] I+ Q3[-,-] I+ Q3[-,-] I- Q3[-,-] I-

9 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Causal Chains Causal path: Influence followed by proportionalities Rare: Multiple influences in a single causal path Impossible: Loop of proportionalities

10 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Multiple Competing Influences CO2 release I+ CO2 Concentration Burning I+ Co2 Concentration Inequality information does not help Burning + CO2 concentration > 0 Introduce Photosynthesis Burning + CO2 < Photosynthesis

11 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Choosing Quantity Spaces Difficult task even for expert modelers Should be behaviorally significant Depends depends on the context: – Phytoplankton blocking sunlight of 1 st producers – Global warming’s effect on phytoplankton

12 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 {Small, Medium, High} considered harmful

13 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Actuators: External actuator (1/3) Models (effect of) process outside the system – Value assignment (MF) – Exogenous behaviour (Scenario) Model by Eugenia Cioaca, Tim Nuttle, Bert Bredeweg

14 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Actuators: Equilibrium Seeking Mechanism (2/3) Models equalizing flows due to potential difference

15 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Actuators: Competing Processes Pattern (3/3) Models competing processes

16 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 States in simulation Maximum number of states: – Cartesian product of all quantities – E.g. Three Q’s: (3x3) 3 =729 (excl. inequalities) Successor states without correspondences: – S-states = 2 q -1, q = non-corresponding quantities

17 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Not all expected states Issue: State is missing Create the state as a scenario – Option 1: No states, state is inconsistent – Option 2: State appears Next create a scenario that generates a previous state Continue to a state in the original simulation

18 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 No States Considered difficult to debug Features: – Inconsistency – > 1 model fragment fired – Clash between contents of: Scenario + MF Multiple MFs Troubleshooting: – Deactivate all MFs (at least 1 state from scenario) – Activate MFs one by one

19 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Inconsistencies Magnitude or derivative value assignments (MF or scenario) Inequalities (MF or Scenario) Operators (plus or minus) Value assignments due to correspondences Value assignments due to influence resolution Exogenous behavior Engine rules Quantity constraints Continuity constraints

20 of 20 23rd Annual Workshop on Qualitative Reasoning (QR 2009) Ljubljana, Slovenia, June , 2009 Conclusions & Future Work Catalog of – Representational issues and their solutions – Frequently occurring patterns – Considerations when debugging Future work: Support in Garp3/DynaLearn – Premade patterns (QS’s and actuators) – Automatic model building – Model diagnosis