Titlebook: Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems; Tatiana Tatarenko Book 2017 Springer International

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書目名稱Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems影響因子(影響力)




書目名稱Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems影響因子(影響力)學(xué)科排名




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書目名稱Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems被引頻次




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孤僻

Ige326

n problems are set without such restrictive assumptions as convexity of the objective functions, complicated communication topologies, closed-form expressions for costs and utilities, and finiteness of the system’s state space.?.978-3-319-88039-6978-3-319-65479-9

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Ejaculate

https://doi.org/10.1007/978-3-642-92345-6Due to the emergence of distributed networked systems, problems of cooperative control in multi-agent systems have gained a lot of attention over the recent years. Some examples of networked multi-agent systems are smart grids, social networks, autonomous vehicle teams, processors in machine learning scenarios, etc.

PAD416

https://doi.org/10.1007/978-3-322-96216-4In this section, a background of the game theory with applications to optimization in multi-agent systems is presented.

grenade

Willi Paul Adams,Erich AngermannThis chapter deals with multi-agent systems whose objective is modeled by means of potential games and which are endowed with . As it was discussed in the previous chapter,

giggle

Amerikastudien / American StudiesThis chapter studies the way to apply stochastic approximation procedure, known as the Robbins–Monro procedure [RM51], to . as well as to . and ..