Evolutionary Multi-Agent Systems [electronic resource] : From Inspirations to Applications /
By: Byrski, Aleksander [author.].
Contributor(s): Kisiel-Dorohinicki, Marek [author.] | SpringerLink (Online service).
Series: Studies in Computational Intelligence: 680Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: XIV, 210 p. 77 illus. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319513881.Subject(s): Computer Engineering
| Computational Intelligence | Artificial Intelligence | Algorithm Analysis and Problem ComplexityDDC classification: 006.3 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.)
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Springer Nature eBookSummary: This book addresses agent-based computing, concentrating in particular on evolutionary multi-agent systems (EMAS), which have been developed since 1996 at the AGH University of Science and Technology in Cracow, Poland. It provides the relevant background information on and a detailed description of this computing paradigm, along with key experimental results. Readers will benefit from the insightful discussion, which primarily concerns the efficient implementation of computing frameworks for developing EMAS and similar computing systems, as well as a detailed formal model. Theoretical deliberations demonstrating that computing with EMAS always helps to find the optimal solution are also included, rounding out the coverage.
This book addresses agent-based computing, concentrating in particular on evolutionary multi-agent systems (EMAS), which have been developed since 1996 at the AGH University of Science and Technology in Cracow, Poland. It provides the relevant background information on and a detailed description of this computing paradigm, along with key experimental results. Readers will benefit from the insightful discussion, which primarily concerns the efficient implementation of computing frameworks for developing EMAS and similar computing systems, as well as a detailed formal model. Theoretical deliberations demonstrating that computing with EMAS always helps to find the optimal solution are also included, rounding out the coverage.
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