
Lectures on Intelligent Systems by Leonardo Vanneschi
This textbook provides the reader with an essential understanding of computational methods for intelligent systems. These are defined as systems that can solve problems autonomously, in particular problems where algorithmic solutions are inconceivable for humans or not practically executable by computers. Despite the rapidly growing applications in this field, the book avoids application details, instead focusing on computational methods that equip the reader with the methodological tools and competencies necessary to tackle current and future complex applications.
The book consists of two parts: computational intelligence methods for optimization, and machine learning. Part I begins with the concept of optimization, and introduces local search algorithms, genetic algorithms, and particle swarm optimization. Part II begins with an introduction to machine learning and covers several methods, many of which can be used as supervised learning algorithms, such as decision treelearning, artificial neural networks, genetic programming, Bayesian learning, support vector machines, and ensemble methods, plus a discussion of unsupervised learning.
This textbook is written in a self-contained style, suitable for undergraduate or graduate students in computer science and engineering, and for self-study by researchers and practitioners.
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Robot Evolution
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An Introduction to Metaheuristics for Optimization
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Deep Neural Evolution
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Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms
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Coevolutionary Computation and Its Applications
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Visions of DNA Nanotechnology at 40 for the Next 40
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Cartesian Genetic Programming
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Bioinspired Computation in Combinatorial Optimization
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Self-organising Software
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Swarm Intelligence
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Evolution as Computation
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Algorithmic Bioprocesses
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General-Purpose Optimization Through Information Maximization
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Nature Inspired Optimisation for Delivery Problems
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Experimental Research in Evolutionary Computation
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Hyper-Heuristics: Theory and Applications
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Modelling in Molecular Biology
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Advances in Metaheuristics for Hard Optimization
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Foraging-Inspired Optimisation Algorithms
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Mobility in Process Calculi and Natural Computing
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Automating the Design of Data Mining Algorithms
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Contemporary Evolution Strategies
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Theory and Principled Methods for the Design of Metaheuristics
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Discrete and Topological Models in Molecular Biology
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Massively Parallel Evolutionary Computation on GPGPUs
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Multimodal Optimization by Means of Evolutionary Algorithms
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Computation in Living Cells
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Sensitivity Analysis for Neural Networks
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Reservoir Computing
“‘Lectures on Intelligent Systems’ provides a nuanced introduction to computational intelligence, balancing foundational topics with deeper dives into specific areas like GA and GP… it encourages further exploration, making it a compelling addition to academic and professional libraries alike. Through their active research, Vanneschi and Silva offer fresh perspectives and authoritative guidance, cementing this text’s place as a recommended resource for anyone venturing into the dynamic landscape of computational intelligence.” (Beatrice M. Ombuki-Berman, Genetic Programming and Evolvable Machines, Vol. 25 (2), 2024)
Sara Silva is a Principal Investigator at the Computer Science and Engineering Research Centre (LASIGE) of the Universidade de Lisboa, Portugal. Her main research interests are machine learning and evolutionary computation, including interdisciplinary applications in the areas of remote sensing and bioinformatics. She is the author of around 100 peer-reviewed publications, having received more than 10 nominations and awards for best paper and best researcher. In 2018 she received the Evo* Award for Outstanding Contribution to Evolutionary Computation in Europe. She created the MATLAB Genetic Programming Toolbox (GPLAB).
| SKU | Unavailable |
| ISBN 13 | 9783031179211 |
| ISBN 10 | 3031179218 |
| Title | Lectures on Intelligent Systems |
| Author | Leonardo Vanneschi |
| Series | Natural Computing Series |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer International Publishing AG |
| Year published | 2023-01-14 |
| Number of pages | 349 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |






























