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Reputational effects, renegotiation and cooperation between the players are analyzed by using formal models.
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Early in his career, Tversky was a "mathematical psychologist," which meant that he used formal models to characterize human behavior.
In this work we present a Model Driven Engineering methodology that addresses validation and verification of security requirements by using formal methods and model transformation algorithms.
They may also use a broader set of models, and use formal model selection criteria (Myhrvold, 2013).
Tools can only be validated using formal proofs if they work on models that are external.
His research interest includes modelling of systems using formal approaches, integration of approaches, safety critical systems.
We use this framework to construct an executable model which is analyzed using formal verification methods.
One of the means that allow modelers to leverage the power of proper modeling techniques (e.g. stochastic techniques) is the application of abstractions by using high level formal modeling languages.
The largest errors are likely biases caused by unmodelled sources (Sabaka et al. 2015) which cannot be assessed using a formal model error covariance matrix, or by constructing models using the same technique from independent datasets.
In addition to validation by domain experts, we used formal analyses to demonstrate the model's self-consistency.
Therefore, we want to compare the mean scores of two rival models by using a formal significance test to assess if score differences are statistically significant on a certain level.
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