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Mean-Field Control for Leader-Follower Multi-Agent Systems

Author(s):

L. Möller
Conference/Journal:

Master Thesis, FS15 (10345)
Abstract:

This thesis considers a mean field game played among a large population of heterogeneous agents that can be divided into two categories: leaders and followers. Each agent is subject to heterogeneous convex constraints and tries to minimize a quadratic cost function that depends on its own strategy and on the population behavior. Specifically, the cost function of each leader is affected by the leaders’ aggregate behavior, while the cost function of each follower is affected by both the leaders’ and the followers’ aggregate behavior. The work proposes several decentralized iterative schemes that, under different conditions on the problem data, are guaranteed to steer the population to a mean-field epsilon-Nash equilibrium of the leader-follower game, with epsilon decreasing linearly to zero as the number of players increases. The theoretical results are illustrated by designing and simulating a demand-response program between electricity consumers and producers in the day-ahead market.

Supervisors: Basilio Gentile, Francesca Parise, Sergio Grammatico, John Lygeros

Year:

2015
Type of Publication:

(12)Diploma/Master Thesis
Supervisor:

J. Lygeros

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2015:IFA_5250
}
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