Algebraic formulation and strategy optimization for a class of evolutionary networked games via semi-tensor product method

Using the semi-tensor product method, this paper investigates the algebraic formulation and strategy optimization for a class of evolutionary networked games with “myopic best response adjustment” rule, and presents a number of new results. First, the dynamics of the evolutionary networked game is c...

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Bibliographic Details
Published in:	Automatica (Oxford) Vol. 49; no. 11; pp. 3384 - 3389
Main Authors:	Guo, Peilian, Wang, Yuzhen, Li, Haitao
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 01.11.2013 Elsevier
Subjects:	Algebra Algebraic formulation Algorithms Applied sciences Computer science; control theory; systems Control system synthesis Control theory. Systems Dynamics Evolutionary Evolutionary networked game Exact sciences and technology Formulations Game theory Games Linear and multilinear algebra, matrix theory Mathematics Operational research and scientific management Operational research. Management science Optimization Sciences and techniques of general use Semi-tensor product Strategy Strategy optimization Semi-tensor product Evolutionary networked game Algebraic formulation Strategy optimization Evolutionary algorithm Myopia Control synthesis Evolutionary game Dynamical system Game theory Optimization Algebraic method Game network Mathematical programming
ISSN:	0005-1098, 1873-2836
Online Access:	Get full text
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