Scardua (134 results)

Paperback. Condition: Very Good. Glendining, Bex; Indigo, Bre; Small, Joshua; White, Kameron; Scárdua, Mariá; Madeline, Morgan; Oyefodunrin, Omotola; Henar, Sonya; Brown, Tanni (illustrator).

paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority. Glendining, Bex; Indigo, Bre; Small, Joshua; White, Kameron; Scárdua, Mariá; Madeline, Morgan; Oyefodunrin, Omotola; Henar, Sonya; Brown, Tanni (illustrator). …

Paperback. Condition: Very Good. Glendining, Bex; Indigo, Bre; Small, Joshua; White, Kameron; Scárdua, Mariá; Madeline, Morgan; Oyefodunrin, Omotola; Henar, Sonya; Brown, Tanni (illustrator).

Condition: good. Glendining, Bex; Indigo, Bre; Small, Joshua; White, Kameron; Scárdua, Mariá; Madeline, Morgan; Oyefodunrin, Omotola; Henar, Sonya; Brown, Tanni (illustrator).

Paperback. Condition: Brand New. 124 pages. 8.00x5.00x0.28 inches. In Stock.

Paperback. Condition: Used; Very Good. **SHIPPED FROM UK** We believe you will be completely satisfied with our quick and reliable service. All orders are dispatched as swiftly as possible! Buy with confidence! Greener Books. Glendining, Bex; Indigo, Bre; Small, Joshua; White, Kameron; Scárdua, Mariá; Madeline, Morgan; Oyefodunrin, Omotola; Henar, Sonya; Brown, Tanni (illustrator). …

Condition: New.

Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condition: New. Print on Demand.

Condition: New.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: As New. Unread book in perfect condition.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

Condition: New.

Condition: New.

Paperback. Condition: new. Paperback. This book meant for those who seek to apply evolutionary algorithms to problems in engineering and science. To this end, it provides the theoretical background necessary to the understanding of the presented evolutionary algorithms and their shortcomings, while also discussing themes that are pivotal to the successful application of evolutionary algorithms to real-world problems. The theoretical descriptions are illustrated with didactical Python implementations of the algorithms, which not only allow readers to consolidate their understanding, but also provide a sound starting point for those intending to apply evolutionary algorithms to optimization problems in their working fields. Python has been chosen due to its widespread adoption in the Artificial Intelligence community. Those familiar with high level languages such as MATLAB will not have any difficulty in reading the Python implementations of the evolutionary algorithms provided in the book.Instead of attempting to encompass most of the existing evolutionary algorithms, past and present, the book focuses on those algorithms that researchers have recently applied to difficult optimization problems, such as control problems with continuous action spaces and the training of high-dimensional convolutional neural-networks. The basic characteristics of real-world optimization problems are presented, together with recommendations on its proper application to evolutionary algorithms. The applied nature of the book is reinforced by the presentation of successful cases of the application of evolutionary algorithms to optimization problems. This is complemented by Python source codes, giving users an insight into the idiosyncrasies of the practical application of evolutionary algorithms. This book meant for students, scientists and engineers to help in the application of evolutionary algorithms to practical optimization problems. The presentation of theoretical background is complemented with didactical Python implementations of evolutionary algorithms that researchers have recently applied to complex optimization problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: New. This book meant for those who seek to apply evolutionary algorithms to problems in engineering and science. To this end, it provides the theoretical background necessary to the understanding of the presented evolutionary algorithms and their shortcomings, while also discussing themes that are pivotal to the successful application of evolutionary algorithms to real-world problems. The theoretical descriptions are illustrated with didactical Python implementations of the algorithms, which not only allow readers to consolidate their understanding, but also provide a sound starting point for those intending to apply evolutionary algorithms to optimization problems in their working fields. Python has been chosen due to its widespread adoption in the Artificial Intelligence community. Those familiar with high level languages such as MATLABT will not have any difficulty in reading the Python implementations of the evolutionary algorithms provided in the book.Instead of attempting to encompass most of the existing evolutionary algorithms, past and present, the book focuses on those algorithms that researchers have recently applied to difficult optimization problems, such as control problems with continuous action spaces and the training of high-dimensional convolutional neural-networks. The basic characteristics of real-world optimization problems are presented, together with recommendations on its proper application to evolutionary algorithms. The applied nature of the book is reinforced by the presentation of successful cases of the application of evolutionary algorithms to optimization problems. This is complemented by Python source codes, giving users an insight into the idiosyncrasies of the practical application of evolutionary algorithms.…

Condition: New.

Paperback. Condition: New.

Condition: New.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New.

Condition: As New. Unread book in perfect condition.

Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.

Condition: New. 2023. 1st Edition. paperback. . . . . .

Condition: New. In English.

Paperback. Condition: New. This book meant for those who seek to apply evolutionary algorithms to problems in engineering and science. To this end, it provides the theoretical background necessary to the understanding of the presented evolutionary algorithms and their shortcomings, while also discussing themes that are pivotal to the successful application of evolutionary algorithms to real-world problems. The theoretical descriptions are illustrated with didactical Python implementations of the algorithms, which not only allow readers to consolidate their understanding, but also provide a sound starting point for those intending to apply evolutionary algorithms to optimization problems in their working fields. Python has been chosen due to its widespread adoption in the Artificial Intelligence community. Those familiar with high level languages such as MATLABT will not have any difficulty in reading the Python implementations of the evolutionary algorithms provided in the book.Instead of attempting to encompass most of the existing evolutionary algorithms, past and present, the book focuses on those algorithms that researchers have recently applied to difficult optimization problems, such as control problems with continuous action spaces and the training of high-dimensional convolutional neural-networks. The basic characteristics of real-world optimization problems are presented, together with recommendations on its proper application to evolutionary algorithms. The applied nature of the book is reinforced by the presentation of successful cases of the application of evolutionary algorithms to optimization problems. This is complemented by Python source codes, giving users an insight into the idiosyncrasies of the practical application of evolutionary algorithms.…

Condition: New.

Condition: New.