| 期刊全称 | Achieving Consensus in Robot Swarms |
| 期刊简称 | Design and Analysis |
| 影响因子2023 | Gabriele Valentini |
| 视频video | http://file.papertrans.cn/144/143850/143850.mp4 |
| 发行地址 | Covers collective decision-making strategies for robot swarms.Focuses on the design of self-organized solutions to the best-of-n problem—the problem of deciding which alternative among a finite set of |
| 学科分类 | Studies in Computational Intelligence |
| 图书封面 |  |
| 影响因子 | .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, usingrobot experiments to show how the designed strategies can be ported to different application scenarios.. |
| Pindex | Book 2017 |
|Archiver|手机版|小黑屋|
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