<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/CINECAstyle.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-22T11:14:41Z</responseDate><request verb="GetRecord" identifier="oai:iris.unitn.it:11572/350780" metadataPrefix="oai_dc">https://iris.unitn.it/oai/request</request><GetRecord><record><header><identifier>oai:iris.unitn.it:11572/350780</identifier><datestamp>2023-12-22T00:06:23Z</datestamp><setSpec>com_11572_237821</setSpec><setSpec>com_11572_101871</setSpec><setSpec>col_11572_237822</setSpec><setSpec>ou_ou00004</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title>Some optimal visiting problems: from a single player to a mean-field type model</dc:title>
<dc:creator>Marzufero, Luciano</dc:creator>
<dc:contributor>Marzufero, Luciano</dc:contributor>
<dc:contributor>Bagagiolo, Fabio</dc:contributor>
<dc:subject>Optimal control</dc:subject>
<dc:subject> optimal stopping</dc:subject>
<dc:subject> optimal switching</dc:subject>
<dc:subject> mean-field game</dc:subject>
<dc:subject> continuity equation</dc:subject>
<dc:subject> transport equation</dc:subject>
<dc:subject> networks</dc:subject>
<dc:subject>Settore MAT/05 - Analisi Matematica</dc:subject>
<dc:description>In an optimal visiting problem, we want to control a trajectory that has to pass as close as possible to a collection of target points or regions. We introduce a hybrid control-based approach for the classic problem where the trajectory can switch between a group of discrete states related to the targets of the problem. The model is subsequently adapted to a mean-field game framework, that is when a huge population of agents plays the optimal visiting problem with a controlled dynamics and with costs also depending on the distribution of the population. In particular, we investigate a single continuity equation with possible sinks and sources and the field possibly depending on the mass of the agents. The same problem is also studied on a network framework. More precisely, we study a mean-field game model by proving the existence of a suitable definition of an approximated mean-field equilibrium and then we address the passage to the limit.</dc:description>
<dc:date>2022-07-19</dc:date>
<dc:type>info:eu-repo/semantics/doctoralThesis</dc:type>
<dc:identifier>http://hdl.handle.net/11572/350780</dc:identifier>
<dc:identifier>http://dx.doi.org/10.15168/11572_350780</dc:identifier>
<dc:identifier>10.15168/11572_350780</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>firstpage:1</dc:relation>
<dc:relation>lastpage:114</dc:relation>
<dc:relation>numberofpages:114</dc:relation>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:publisher>Università degli studi di Trento</dc:publisher>
<dc:publisher>place:TRENTO</dc:publisher>
<dc:rights>license:Creative commons</dc:rights>
<dc:rights>license uri:http://creativecommons.org/licenses/by-nd/4.0/</dc:rights>
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