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From Genetic Variation to Probabilistic Modeling
Genetic algorithms ⦓GAs) [53, 83] are stochastic optimization methods inspired by natural evolution and genetics. Over the last few decades, GAs have...
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Hierarchical Bayesian Optimization Algorithm
The previous chapter has discussed how hierarchy can be used to reduce problem complexity in black-box optimization. Additionally, the chapter has...
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The Challenge of Hierarchical Difficulty
Thus far, we have examined the Bayesian optimization algorithm (BOA), empirical results of its application to several problems of bounded difficulty,...
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Hierarchical BOA in the Real World
The last chapter designed hBOA, which was shown to provide scalable solution for hierarchical traps. Since hierarchical traps were designed to test...
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Scalability Analysis
The empirical results of the last chapter were tantalizing. Easy and hard problems were automatically solved without user intervention in polynomial...
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Summary and Conclusions
The purpose of this chapter is to provide a summary of main contributions of this work and outline important conclusions.
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Bayesian Optimization Algorithm
The previous chapter argued that using probabilistic models with multivariate interactions is a powerful approach to solving problems of bounded...
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Probabilistic Model-Building Genetic Algorithms
The previous chapter showed that variation operators in genetic and evolutionary algorithms can be replaced by learning a probabilistic model of...
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Systematizing modeler experience (MX) in model-driven engineering success stories
Modeling is often associated with complex and heavy tooling, leading to a negative perception among practitioners. However, alternative paradigms,...
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iDOCEM
In the business process lifecycle, models can be approached from two perspectives: on the one hand, models are used to create systems in the design...
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Requirements for modelling tools for teaching
Modelling is an important activity in software development and it is essential that students learn the relevant skills. Modelling relies on dedicated...
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Real-time scheduling of power grid digital twin tasks in cloud via deep reinforcement learning
As energy demand continues to grow, it is crucial to integrate advanced technologies into power grids for better reliability and efficiency. Digital...
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ASOD: an adaptive stream outlier detection method using online strategy
In the current era of information technology, blockchain is widely used in various fields, and the monitoring of the security and status of the...
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SymboleoPC: checking properties of legal contracts
Legal contracts specify requirements for business transactions. Symboleo was recently proposed as a formal specification language for legal...
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Guest editorial to the special section on PoEM’2022
This guest editorial presents the papers contributing to the 15th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modelling (PoEM 2022)....
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Automated generation of smart contract code from legal contract specifications with Symboleo2SC
Smart contracts (SCs) are software systems that monitor and partially control the execution of legal contracts to ensure compliance with the...
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Human factors in model-driven engineering: future research goals and initiatives for MDE
Software modelling and model-driven engineering (MDE) is traditionally studied from a technical perspective. However, one of the core motivations...
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Computational intelligence-based classification system for the diagnosis of memory impairment in psychoactive substance users
Computational intelligence techniques have emerged as a promising approach for diagnosing various medical conditions, including memory impairment....
