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Toward a theory of modeling
Which kind of Models??
• There are different understanding of the term Model in different disciplines
Modeling
Application-Domain specific level
Technical level
Abstract level
Modeling ProblemsAbstract Level
Definition-1: A model M ={ G, F, R}G= goal(s) for modelingF=Candidate (observable or controllable)features or properties from the real systemR= Possible Relations between elements of FAssumption: We observe and construct objects based on properties.
Application-Domain specific level
Technical level
Abstract level
Modeling ProblemsAbstract Level
Definition-1: A model M ={ G, F, R}G= goal(s) for modelingF=Candidate (observable or controllable)features or properties from the real systemR= Possible Relations between elements of FAssumption: We observe and construct objects based on properties.
Definition-2: A dynamic model M is a model, with varying element(s). Definition-3: Model Complexity: ???Definition-4: Model sufficiency:???Definition-5: Model accuracy:???Definition-6: Model validation and model-ability measure :???Definition-6: Model ???• Selection of a model should be based on the above mentioned measures from definition 2,
onwardsSo in the next level, we will possibly have several classes of technical modeling problems and modeling approaches based on different combinations of these
elements
Application-Domain specific level
Technical level
Abstract level
Modeling ProblemsTechnical Level
Application-Domain specific level
Technical level
Abstract level
Clustering
Possible Technical Modeling Problems, based on different goals.
Modeling ProblemsTechnical Level
Application-Domain specific level
Technical level
Abstract level
Possible Technical Modeling Problems, based on different goals.
Modeling ProblemsApplication-Domain specific leve
Technical level
Abstract level
Then, Application-Domain Specific problems can be considered as a combination of one or more categories of technical problems.
Building Management System
Design
Optimization
A few examples
Modeling approaches(How we approach the problems?)
• Linearity Vs. Non-linearity
• Specific Vs. Pre-specific (explicit models vs. environment for possible/probable explicit models)
• Model separate than Real phenomenon vs. Model as a Part of the real system. (e.g. simulated agents or real connected actors)
Modeling(virtual reality)
So Far, …Modeling as a separate Reality
Reality
Analysis
Synthesis
Optimization & Design
It is the Story of Elephant in the Dark RoomWhich Model is the best?
(e.g. : which approach is better for modeling urban environment?)
Single Disciplinary Methods. (e.g. Analytical)Multidisciplinary and Interdisciplinary models (Stocks and Flows, Urban
Metabolism)
Model as a part of Reality
Modeling
Reality• We can’t Model the elephant.
Since the elephant, itself is evolving!!
• We no longer model Agents explicitly. We let them play.
• To Provide an environment for real agents instead of simulated agents!
• And this is happening with emerging technologies in ICT: e.g. Crowd sourcing, Pervasive Data Collection, Eigen-Behavior Monitoring,…
Model is a part of the everyday life.We just collect Data through social MediaWe Process data to find evolving patterns, vs, rigid Categories.We inform stakeholders And they will evolve themselves.
Model as a part of Reality
Modeling
Reality
And the main Elements will be:
Coding, Communication and Data Modeling.
Network Theory
Data Processing and Modeling
Algebra
Associative Networks (SOM)
Structured DBs
Un-Structured DBs (Text, Audio, Video, Image,…)
What we need is Mathematics as the art of learning :
So, What next?
• Developing a Formalized Mathematical model for “modeling” to
– Be able to categorize the real world problems, based on modeling point of view
– Advise about model complexity, model-ability,…
• Developing a practical toolbox for modeling based on the categories in the technical level.
Some points
• We are no-longer dependent to classic academic disciplines, since we have a new cut!?
• Theory-Driven Vs. Data Driven Modeling
