Share
Principles in Noisy Optimization: Applied to Multi-Agent Coordination (Cognitive Intelligence and Robotics) (in English)
Pratyusha Rakshit; Amit Konar (Author)
·
Springer
· Hardcover
Principles in Noisy Optimization: Applied to Multi-Agent Coordination (Cognitive Intelligence and Robotics) (in English) - Pratyusha Rakshit; Amit Konar
$ 104.20
$ 109.99
You save: $ 5.79
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My WishlistsIt will be shipped from our warehouse between
Monday, June 17 and
Tuesday, June 18.
You will receive it anywhere in United States between 1 and 3 business days after shipment.
Synopsis "Principles in Noisy Optimization: Applied to Multi-Agent Coordination (Cognitive Intelligence and Robotics) (in English)"
Noisy optimization is a topic of growing interest for researchers working on mainstream optimization problems. Although several techniques for dealing with stochastic noise in optimization problems are covered in journals and conference proceedings, today there are virtually no books that approach noisy optimization from a layman’s perspective; this book remedies that gap. Beginning with the foundations of evolutionary optimization, the book subsequently explores the principles of noisy optimization in single and multi-objective settings, and presents detailed illustrations of the principles developed for application in real-world multi-agent coordination problems. Special emphasis is given to the design of intelligent algorithms for noisy optimization in real-time applications. The book is unique in terms of its content, writing style and above all its simplicity, which will appeal to readers with a broad range of backgrounds.The book is divided into 7 chapters, the first of which provides an introduction to Swarm and Evolutionary Optimization algorithms. Chapter 2 includes a thorough review of agent architectures for multi-agent coordination. In turn, Chapter 3 provides an extensive review of noisy optimization, while Chapter 4 addresses issues of noise handling in the context of single-objective optimization problems. An illustrative case study on multi-robot path-planning in the presence of measurement noise is also highlighted in this chapter. Chapter 5 deals with noisy multi-objective optimization and includes a case study on noisy multi-robot box-pushing. In Chapter 6, the authors examine the scope of various algorithms in noisy optimization problems. Lastly, Chapter 7 summarizes the main results obtained in the previous chapters and elaborates on the book’s potential with regard to real-world noisy optimization problems.
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
✓ Producto agregado correctamente al carro, Ir a Pagar.