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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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Approaching the Concept of Competency
The concept of competency is one of the core elements in this book. For this reason, it is crucial to illustrate several approaches to the definition...
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Data Gathering of Guided Expert Interviews
In addition to the gathering and analysis of curricula data, guided interviews with experts were conducted to identify further competencies expected...
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Functions
This chapter introduces the concept of functions, a cornerstone of computer programming, essential for code organization and reusability. Functions...
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Moderate Examples
This chapter is focused on the importance of moderate examples in the learning curve of programming with MATLAB. Situated between basic tutorials and...
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Loops
This chapter explains the significance of loops within computational theory and computer programming, highlighting their role as fundamental...
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Traversal of Multidimensional Arrays
Here, we explore the critical operation of traversing multidimensional arrays in computer programming, a task central to handling complex data...
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Arrays
This chapter presents the fundamental role of arrays within data structures, highlighting their critical function in the organized management of...
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Conditional Branching
This chapter focuses on the critical role of decision-making in source code through conditional branching, a cornerstone of computer science and...
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Matrix Operations
This chapter discusses the essence of matrix operations, a cornerstone in the field of mathematics and applied sciences such as linear algebra,...
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Traversal of Multidimensional Arrays
This chapter focuses on the essential techniques for traversing multidimensional arrays in computer programming, a key operation when handling...
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Conditional Branching
This chapter shows the essential concept of conditional branching in computer science, underscoring its role in enabling dynamic decision-making...