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...
Κύριος συγγραφέας: | Tatarenko, Tatiana (Συγγραφέας) |
---|---|
Συγγραφή απο Οργανισμό/Αρχή: | SpringerLink (Online service) |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2017.
|
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Παρόμοια τεκμήρια
-
Explorations in Monte Carlo Methods
ανά: Shonkwiler, Ronald W., κ.ά.
Έκδοση: (2009) -
Advances in Dynamic Games Applications to Economics, Finance, Optimization, and Stochastic Control /
Έκδοση: (2005) -
Stochastics of Environmental and Financial Economics Centre of Advanced Study, Oslo, Norway, 2014-2015 /
Έκδοση: (2016) -
Continuous-time Stochastic Control and Optimization with Financial Applications
ανά: Pham, Huyên
Έκδοση: (2009) -
General Pontryagin-Type Stochastic Maximum Principle and Backward Stochastic Evolution Equations in Infinite Dimensions
ανά: Lü, Qi, κ.ά.
Έκδοση: (2014)