Vpliv mešanja in kompleksnih interakcij na razvoj sodelovanja v igri javnih dobrin : doktorska disertacija po skandinavskem modelu

Duh, Maja

| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

First page > Show document

Show document

Title:	Vpliv mešanja in kompleksnih interakcij na razvoj sodelovanja v igri javnih dobrin : doktorska disertacija po skandinavskem modelu
Authors:	ID Duh, Maja (Author) ID Perc, Matjaž (Mentor) More about this mentor... ID Gosak, Marko (Comentor)
Files:	DOK_Duh_Maja_2024.pdf (15,83 MB) MD5: 0E9D6F44CD4E0BAF4565CFBDF9C40E20
Language:	Slovenian
Work type:	Doctoral dissertation
Typology:	2.08 - Doctoral Dissertation
Organization:	FNM - Faculty of Natural Sciences and Mathematics
Abstract:	Razumevanje razvoja sodelovanja med posamezniki, ki so v osnovi sebični, je eden najpomembnejših izzivov današnjega časa, ki vzbuja zanimanje raziskovalcev iz različnih področij. V ta namen znanstveniki integrirajo evolucijsko teorijo iger z naprednimi metodami s področja znanosti o omrežjih in metodami statistične fizike. V doktorski disertaciji smo s pomočjo takega interdisciplinarnega pristopa raziskali, kako različni tipi mobilnosti oziroma mešanj igralcev na različnih interakcijskih mrežah vplivajo na evolucijo in promocijo sodelovanja v igri javnih dobrin. V ta namen smo raziskovalno delo razdelili v štiri sklope. V prvem delu smo pokazali, da uvedba mešanja igralcev v igri javnih dobrin na regularnem omrežju omogoči prehod iz stanja sistema vpetega v prostorsko mrežo v stanje dobro mešane populacije, kjer struktura interakcijske mreže več nima bistvenega pomena na evolucijsko dinamiko. Izkaže se, da je v primeru mešanja najbližjih sosedov za to potrebna večja frekvenca mešanja kot pri mešanju naključnih igralcev. Nadalje smo pokazali, da oba načina mešanja zavirata evolucijski uspeh kooperatorjev. V nadaljevanju smo raziskavo razširili na področje kompleksnih omrežij, ki podajajo realnejši opis interakcij med posamezniki. V drugem delu doktorske disertacije smo tako igro javnih dobrin postavili na naključno omrežje, vpeto v hiperbolični prostor in v model vključili asortativno in disasortativno mešanje igralcev. Ugotovili smo, da oba tipa mešanja zavirata razvoj sodelovanja ne glede na arhitekturo omrežja, a je vpliv disasortativnega mešanja večji v primerjavi z asortativnim mešanjem. Naslednji tip interakcijske mreže, s katerim se še boljše opišemo realne interakcije, so večplastna soodvisna omrežja, ki smo jih v raziskave vključili v naših naslednjih dveh raziskavah. Soodvisnost med dvema omrežjema smo vpeljali s koristnostno funkcijo in pokazali, da lahko parameter pristranskosti učinkovito vpliva na raven sodelovanja. Pokazali smo, da asortativne medmrežne povezave med dvema skalno neodvisnima omrežjema spodbujajo kooperacijo v igri javnih dobrin v nekoliko večji meri kot naključne in disasortativne povezave. V zadnjem sklopu raziskav smo prišli do presenetljivih zaključkov. Rezultati mešanja na dvoplastnem soodvisnem omrežju, kjer posamezna plast predstavlja naključno omrežje, vpeto v hiperbolični prostor, kažejo, da lahko mešanje znotraj posamezne plasti omrežja, kjer je sodelovanje prvotno uspešno, močno oslabi evolucijsko uspešnost kooperatorjev na tej plasti, medtem ko jo za določene vrednosti normaliziranega sinergijskega faktorja spodbuja sodelovanje na drugi plasti omrežja. Rezultati doktorske disertacije predstavljajo pomemben prispevek k znanstvenemu raziskovanju na področju razumevanja razvoja in vzdrževanja sodelovanja, s poudarkom na uporabi evolucijske teorije iger, kompleksnih omrežij in mobilnosti igralcev.
Keywords:	evolucijska teorija iger, igra javnih dobrin, sodelovanje, mešanje, kompleksna omrežja, večplastna omrežja, simulacije Monte Carlo
Geographic coverage:	Slovenija;
Place of publishing:	Maribor
Place of performance:	Maribor
Publisher:	[M. Duh]
Year of publishing:	2024
Number of pages:	XIV, 96 str.
PID:	20.500.12556/DKUM-87026
UDC:	519.83(043.3)
COBISS.SI-ID:	197778947
Publication date in DKUM:	05.06.2024
Views:	279
Downloads:	79
Metadata:
Categories:	FNM
:	Copy citation

Average score:	(0 votes)
Your score:	Voting is allowed only for logged in users.
Share:

Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

Licences

License:	CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	09.02.2024

Secondary language

Language:	English
Title:	Effects of mixing and complex interactions on the evolution of cooperation in the public goods game
Abstract:	Understanding the evolution of cooperation among otherwise selfish individuals is one of the most significant challenges of our time, attracting researchers from various fields. To address this, scientists integrate evolutionary game theory with advanced methods from network science and statistical physics. In the doctoral dissertation, we utilize such an interdisciplinary framework to explore the impact of various player mobilities or mixtures on different interaction networks on the evolution and promotion of cooperation in a public goods game. For this purpose, our research was divided into four sections. In the first part, we showed that introducing mixing of players in public goods games on a regular network facilitates a transition from a system embedded in a spatial network to a state of a well-mixed population, where the structure of the interaction network no longer significantly affects the evolutionary dynamics. Notably, we find that for nearest-neighbor mixing, a higher mixing frequency is required compared to random mixing. Moreover, both types of mixing hinder the evolutionary success of cooperators. Subsequently, our focus shifts to complex networks, effectively capturing essential structural properties of real-world interactions. In the second part of the doctoral dissertation, we thus placed the public goods game on random geometric graphs embedded into hyperbolic spaces and incorporated assortative and disassortative mixing of players into the model. Results indicate that both types of mixing impair the evolution of cooperation regardless of the network architecture. Furthermore, disassortative mixing is more detrimental for cooperation compared with assortative mixing. The next type of interaction networks that closely approximate real interactions are multilayer interdependent networks, which we included in our next two studies. We introduced interdependence between two networks using a utility function and showed that the bias parameter effectively influences the level of cooperation. We demonstrated that assortative linking between two scale-free networks promote cooperation in public goods games with a relatively modest margin in comparison to random and disassortative matching between the two layers. In the last part of our research, we have drawn noteworthy and unexpected conclusions. The outcomes of mixing on a two-layer interdependent network, where each layer represents a random geometric graph in hyperbolic space, reveal that mixing on a network where cooperation is primary successful, impairs the evolutionary success of cooperators on the same network layer. However, for certain values of the normalized synergy factor, it promotes cooperation on the other network layer. The results of the doctoral dissertation constitute a substantial contribution to scientific research in understanding the evolution and maintenance of cooperation, emphasizing the utilization of evolutionary game theory, complex networks, and the mobility of players.
Keywords:	evolutionary game theory, public goods game, cooperation, mixing, complex networks, multilayer networks, Monte Carlo simulations

Comments

Leave comment

You must log in to leave a comment.

Comments (0)

0 - 0 / 0

There are no comments!

Back