Distributed Seeking of Nash Equilibria With Applications to Mobile Sensor Networks

We consider the problem of distributed convergence to a Nash equilibrium in a noncooperative game where the players generate their actions based only on online measurements of their individual cost functions, corrupted with additive measurement noise. Exact analytical forms and/or parameters of the...

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Veröffentlicht in:	IEEE transactions on automatic control Jg. 57; H. 4; S. 904 - 919
Hauptverfasser:	Stankovic, M. S., Johansson, K. H., Stipanovic, D. M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.04.2012 Institute of Electrical and Electronics Engineers
Schlagworte:	Algorithm design and analysis Applied sciences Artificial intelligence Computer science; control theory; systems Computer systems and distributed systems. User interface Convergence Cost function Exact sciences and technology extremum seeking Game theory Games Heuristic algorithms learning mobile sensor networks multi-agent control Nash equilibrium Noise noncooperative games Operational research and scientific management Operational research. Management science Software SRA - ICT SRA - Informations- och kommunikationsteknik stochastic optimization Nash strategy Extreme search Nash equilibrium learning Fork join problem Modeling Adaptive method Convergence stochastic optimization multi-agent control Non cooperative game Kinematics Cost function Integrator Game equilibrium Additive noise Almost sure convergence Probabilistic approach Coordination Non holonomic system mobile sensor networks noncooperative games Game theory extremum seeking Stochastic programming Multiagent system Discrete time Problem solving Wireless network Sensor array Artificial intelligence Mobile computing
ISSN:	0018-9286, 1558-2523, 1558-2523
Online-Zugang:	Volltext
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