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Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems

This book presents new efficient methods for optimization in realistic large-scale, multi-agent systems. These methods do not require the agents to have the full information about the system, but instead allow them to make their local decisions based only on the local information, possibly obtained...

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Bibliographic Details
Main Author:	Tatarenko, Tatiana, 1989-
Corporate Author:	SpringerLink (Online service)
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing : Imprint : Springer, 2017. Cham : 2017.
Physical Description:	1 online resource (IX, 171 pages 38 illustrations) : online resource.
Subjects:	Mathematics. Computer science -- Mathematics. System theory. Mathematical optimization. Probabilities. Statistics. Game theory. Machine learning. Multiagent systems. Mathematics. Game theory. Computer science -- Mathematics. Stochastic processes.
Online Access:	SpringerLink - Click here for access

Game-theoretic learning and distributed optimization in memoryless multi-agent systems by Tatarenko, Tatiana, 1989-

Published: Springer, 2017

Description: 1 online resource.

SpringerLink - Click here for access

Electronic eBook

Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems

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