Achieving consensus in robot swarms : design and analysis of strategies for the best-of-n problem

This book focuses on the design and analysis of collective decision-making strategies for the best-of-n problem. After providing a formalization of the structure of the best-of-n problem supported by a comprehensive survey of the swarm robotics literature, it introduces the functioning of a collecti...

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Bibliographic Details
Main Author: Valentini, Gabriele, (Author)
Format: eBook
Language: English
Published: Cham, Switzerland : Springer, 2017.
Series: Studies in computational intelligence ; v. 706.
Subjects:
Swarm intelligence.
Robotics.
elektronické knihy
electronic books
ISBN: 9783319536095
9783319536088
Physical Description: 1 online resource (xiv, 146 pages) : illustrations (some color)

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100 1 |a Valentini, Gabriele,  |e author. 
245 1 0 |a Achieving consensus in robot swarms :  |b design and analysis of strategies for the best-of-n problem /  |c Gabriele Valentini. 
264 1 |a Cham, Switzerland :  |b Springer,  |c 2017. 
300 |a 1 online resource (xiv, 146 pages) :  |b illustrations (some color) 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
490 1 |a Studies in computational intelligence,  |x 1860-949X ;  |v volume 706 
504 |a Includes bibliographical references. 
505 0 |a Introduction -- Part 1:Background and Methodology -- Discrete Consensus Achievement in Artificial Systems -- Modular Design of Strategies for the Best-of-n Problem -- Part 2:Mathematical Modeling and Analysis -- Indirect Modulation of Majority-Based Decisions -- Direct Modulation of Voter-Based Decisions -- Direct Modulation of Majority-Based Decisions -- Part 3:Robot Experiments -- A Robot Experiment in Site Selection -- A Robot Experiment in Collective Perception -- Part 4:Discussion and Annexes -- Conclusions -- Background on Markov Chains. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a This book focuses on the design and analysis of collective decision-making strategies for the best-of-n problem. After providing a formalization of the structure of the best-of-n problem supported by a comprehensive survey of the swarm robotics literature, it introduces the functioning of a collective decision-making strategy and identifies a set of mechanisms that are essential for a strategy to solve the best-of-n problem. The best-of-n problem is an abstraction that captures the frequent requirement of a robot swarm to choose one option from of a finite set when optimizing benefits and costs. The book leverages the identification of these mechanisms to develop a modular and model-driven methodology to design collective decision-making strategies and to analyze their performance at different level of abstractions. Lastly, the author provides a series of case studies in which the proposed methodology is used to design different strategies, using robot experiments to show how the designed strategies can be ported to different application scenarios. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Swarm intelligence. 
650 0 |a Robotics. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Print version:  |a Valentini, Gabriele.  |t Achieving consensus in robot swarms.  |d Cham, Switzerland : Springer, 2017  |z 3319536087  |z 9783319536088  |w (OCoLC)968663431 
830 0 |a Studies in computational intelligence ;  |v v. 706.  |x 1860-949X 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://link.springer.com/10.1007/978-3-319-53609-5  |y Plný text 
992 |c NTK-SpringerENG 
999 |c 99831  |d 99831 
993 |x NEPOSILAT  |y EIZ 

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