Game Theory and Dynamic Mechanisms on Graphs

Λαγός, Αθανάσιος-Ραφαήλ; Lagos, Athanasios-Rafail

dc.contributor.author	Λαγός, Αθανάσιος-Ραφαήλ	el
dc.contributor.author	Lagos, Athanasios-Rafail	en
dc.date.accessioned	2023-03-13T08:23:25Z
dc.date.available	2023-03-13T08:23:25Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/57236
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.24934
dc.rights	Αναφορά Δημιουργού - Μη Εμπορική Χρήση - Παρόμοια Διανομή 3.0 Ελλάδα	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/3.0/gr/	*
dc.subject	Game Theory	en
dc.subject	Opinion dynamics	el
dc.subject	Epidemic dynamics	el
dc.subject	Decentralised control	el
dc.subject	Multiagent systems	el
dc.title	Game Theory and Dynamic Mechanisms on Graphs	en
heal.type	doctoralThesis
heal.classification	Electrical and Computer Engineering	en
heal.classification	Mathematics	el
heal.language	en
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2022-12-16
heal.abstract	In this thesis, game theoretic and control methods have been applied in problems arising in decentralised networked systems. Three applications have been considered. The first deals with opinion dynamics and manipulation in social networks. The second is related to the spontaneous response of a population to an epidemic outbreak through social distancing. The third introduces a stochastic consensus protocol for finite-time coordination of agents with high-order dynamics. In these three applications, the structure of the system is interconnected, the agents possess some kind of intelligence and act in a decentralised way. So, either game situations arise and the equilibria are studied or decentralised control protocols are necessary to achieve some collective goal. In the first application, a social choice procedure is modeled as a Nash game among the agents. The agents are communicating with each other through a communication network e.g., a social network, modeled by an undirected graph and their opinions follow a dynamic rule modelling conformity. The agents’ criteria for this game are describing a trade off between self-consistent and manipulative behaviors. Their best response strategies are resulting in a dynamic rule for their actions. The stability properties of these dynamics are studied. In the case of instability, which arises when the agents are highly manipulative, the stabilization of these dynamics through the design of the network topology is formulated as a constrained integer programming problem. The constraints have the form of a Bilinear Matrix Inequality (BMI), which is known to result in a nonconvex feasible set in the general case. To deal with this problem a genetic algorithm, which uses a Linear Matrix Inequality (LMI) solver during the selection procedure, is designed. The second application deals with the choice of a population to apply social distancing, which is modeled as a Nash game where the agents determine their social interactions. The interconnections among the agents are modeled by a network. The information available to the agents plays a crucial role. Two information patterns are examined, the case that the agents know exactly the health states of their neighbors and the case they have only statistical information for the global prevalence of the epidemic. The agents are considered to be myopic, and thus, the Nash equilibria of static games for each day are studied. The Nash equilibria are characterized and algorithms are introduced to compute them. Moreover, the effects of the network structure, the virus transmissibility, the number of vulnerable agents, the health care system capacity and the information quality (fake news) are examined through simulations. In the third application a novel stochastic minimum-maximum consensus protocol is introduced and analyzed. The stochastic mixing and the low computational effort make this protocol well suited for secure consensus in cyber-physical systems, composed by autonomous agents with limited resources. It is proven that the protocol converges almostsurely in finite time. Furthermore, the application of the stochastic consensus protocol coupled with a finite-time control law on a distributed system of agents with high-order dynamics is considered and it is proven that the agents’ states converge in finite time. Finally, simulations showing the efficiency of this decentralised finite-time control scheme on doubleintegrator agents are presented.	en
heal.advisorName	Παπαβασσιλόπουλος. Γεώργιος	el
heal.advisorName	Papavassilopoulos, George	en
heal.committeeMemberName	Papavassilopoulos, George	el
heal.committeeMemberName	Maragos, Petros	el
heal.committeeMemberName	Psillakis, Charalampos	el
heal.committeeMemberName	Maratos, Nikolaos	el
heal.committeeMemberName	Papavassileiou, Symeon	el
heal.committeeMemberName	Tzafestas, Kostantinos	el
heal.committeeMemberName	Tsinias, Ioannis	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών	el
heal.academicPublisherID	ntua
heal.fullTextAvailability	false