國立虎尾科技大學 |

Principles in noisy optimization = applied to multi-agent coordination /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Principles in noisy optimization/ by Pratyusha Rakshit, Amit Konar.
其他題名:	applied to multi-agent coordination /
作者:	Rakshit, Pratyusha.
其他作者:	Konar, Amit.
出版者:	Singapore :Springer Singapore : : 2018.,
面頁冊數:	xvi, 367 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Mathematical optimization. -
電子資源:	https://doi.org/10.1007/978-981-10-8642-7
ISBN:	9789811086427

Principles in noisy optimization = applied to multi-agent coordination /
Rakshit, Pratyusha.

Principles in noisy optimizationapplied to multi-agent coordination /[electronic resource] :by Pratyusha Rakshit, Amit Konar. - Singapore :Springer Singapore :2018. - xvi, 367 p. :ill. (some col.), digital ;24 cm. - Cognitive intelligence and robotics,2520-1956. - Cognitive intelligence and robotics..

Chapter 1. Foundations in Evolutionary Optimization Algorithms -- Chapter 2. Multi-agent Coordination -- Chapter 3. Evolutionary Algorithms in Presence of Noise -- Chapter 4. Learning based Noisy Optimization -- Chapter 5. Noisy Coordination in Multi-objective Settings -- Chapter 6. Integrating Principles of Noisy Optimization with Evolutionary Optimization -- Chapter 7. Conclusion and Future Direction.

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.

ISBN: 9789811086427

Standard No.: 10.1007/978-981-10-8642-7doiSubjects--Topical Terms:

527675
Mathematical optimization.

LC Class. No.: QA402.5

Dewey Class. No.: 519.6

Principles in noisy optimization = applied to multi-agent coordination /
LDR:03329nam a2200337 a 4500 001 930090
003 DE-He213
005 20181119232209.0
006 m d
007 cr nn 008maaau
008 190627s2018 si s 0 eng d
020 $a 9789811086427 $q (electronic bk.)
020 $a 9789811086410 $q (paper)
024 7 $a 10.1007/978-981-10-8642-7 $2 doi
035 $a 978-981-10-8642-7
040 $a GP $c GP
041 0 $a eng
050 4 $a QA402.5
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 519.6 $2 23
090 $a QA402.5 $b .R162 2018
100 1 $a Rakshit, Pratyusha. $3 1211063
245 1 0 $a Principles in noisy optimization $h [electronic resource] : $b applied to multi-agent coordination / $c by Pratyusha Rakshit, Amit Konar.
260 $a Singapore : $c 2018. $b Springer Singapore : $b Imprint: Springer,
300 $a xvi, 367 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Cognitive intelligence and robotics, $x 2520-1956
505 0 $a Chapter 1. Foundations in Evolutionary Optimization Algorithms -- Chapter 2. Multi-agent Coordination -- Chapter 3. Evolutionary Algorithms in Presence of Noise -- Chapter 4. Learning based Noisy Optimization -- Chapter 5. Noisy Coordination in Multi-objective Settings -- Chapter 6. Integrating Principles of Noisy Optimization with Evolutionary Optimization -- Chapter 7. Conclusion and Future Direction.
520 $a 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.
650 0 $a Mathematical optimization. $3 527675
650 0 $a Multiagent systems. $3 745736
650 1 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Optimization. $3 669174
650 2 4 $a Theory of Computation. $3 669322
700 1 $a Konar, Amit. $3 671252
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
830 0 $a Cognitive intelligence and robotics. $3 1207079
856 4 0 $u https://doi.org/10.1007/978-981-10-8642-7
950 $a Computer Science (Springer-11645)