Univerza na Primorskem Fakulteta za management
Več informacij o projektu / More info about the project
Naslov
Title
SLO:
Fazni prehodi proti koordinaciji v večplastnih omrežjih
EN:
Phase transitions towards coordination in multilayer networks
Akronim
Acronym
J1-2457
Vodilna institucija
Leading institution
UM Fakulteta za naravoslovje in matematiko
Partnerske institucije
Partner institutions
Institut »Jožef Stefan«,
Vodja projekta
Project leader
Matjaž Perc
Financer projekta
Funding Organization
/
Vrsta projekta
Project Type
Temeljni projekt
Trajanje
Duration
09.01.2020 – 03.11.2026
Spletna stran projekta
Project website
Oddelek
Department
FM
Opis / Description
Opis
Description
SLO:
DP3: Identifikacija in klasifikacija faznih prehodov v koevolucijskih modelih, kjer interakcije med omrežji vplivajo na matriko izplačil in funkcijo koristnosti konkurenčnih igralcev. Cilj je temeljito razumeti, kako interakcije med omrežji vplivajo na sposobnost posameznih igralcev in kako razlike na mikro ravni vplivajo na makroskopsko stanje sistema. Pričakuje se, da bo ločitev časovnih skal med različnimi mikroskopskimi procesi, kot sta interakcija in posvojitev, ključni element, ki vpliva na makroskopsko opazne interakcije med različnimi plastmi omrežja. Temeljno vprašanje je, kako koevolucija takšne soodvisnosti vodi do pojava pristranskih koristnosti in kateri fazni prehodi so vključeni.
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Koordinacija je organizacija različnih elementov kompleksnega sistema z namenom, da je njegovo kolektivno delovanje učinkovito. Kot takšna, koordinacija zajema širok spekter različnih procesov, vključujoč sodelovanje, sinhronizacijo, in tvorjene vzorcev. Sodelovanje je najpomembnejši izziv s katerim se sooča Darwinova teorija evolucije in le-to je bistveno za razumevanje glavnih evolucijskih prehodov, ki so vodili od enoceličnih organizmov do kompleksnih živalskih in človeških družb. Če preživijo le najmočnejši, zakaj naj bi nek organizem izvajal nesebično dejanje, ki koristi pa drugemu? Sinhronizacija in tvorjenje vzorcev, po drugi strani, pa sta med najbolj izstopajočimi in univerzalnimi pojavi v nelinearni znanosti kakor tudi v tekočih kristalih. Metode neravnovesne statistične fizike, še posebej kolektivno obnašanje delcev v interakciji blizu faznih prehodov, so se šele pred kratkim izkazale kot neprecenljive za razumevanje koordiniranih izidov v kompleksnih sistemih na večplastnih omrežjih. Pomembno je, da več-točkovne interakcije, ki so vključene v tovrstne procese, povzročajo kritično obnašanje, ki po svoji kompleksnosti prekaša kar je doslej znanega o interakcijah v parih, ki jih tipično najdemo v sistemih fizike trdne snovi. Nepopolnost obstoječe teorije je nadalje še izrazitejša pri interakcijah med omrežji, ki povzročajo medsebojne soodvisnosti na večih nivojih, kar pa lahko sproži soodvisne napake in pospeši nenadne prehode k celo-sistemskim katastrofam. Naš namen je koristno uporabiti in razširiti koncept faznih prehodov in univerzalnosti tako, da bo postal primeren za opisovanje in razlago pojava koordinacije v večplastnih omrežjih. Razvili bomo široko uporabne teoretične osnove, ki bodo odprle nova obzorja na poti k razumevanju, predvidevanju in nadziranju bogate raznolikosti pomembnih pojavov, ki so odvisni od koordinacije. Vse od sodelovanja v človeški družbi do tvorjenja vzorcev v tekoče-kristalnih filmih do boljšega vrednotenja znanosti, obljuba dobrega teoretičnega razumevanja faznih prehodov, ki vodijo do koordinacije v večplastnih omrežjih bo imela široko stimulativne učinke v teoretični in statistični fiziki.
Faze projekta in njihova realizacija
DP1: Želimo razumeti, kako lokalne topološke značilnosti interakcijskih omrežij vplivajo na nastanek koordinacije prek odločitev posameznih agentov, ko ustvarjajo in prekinjajo povezave z drugimi člani v večplastni strukturi. Tukaj lahko nadaljujemo z našimi obstoječimi raziskovalnimi prizadevanji, ki so opredelila ključne koevolucijske procese, ki bi lahko olajšali sodelovanje in sinhronizacijo, kot pomembne primere koordinacije. Očitni cilj je razširiti to teorijo na večplastna omrežja, kjer so določeni akterji člani dveh ali več različnih, a medsebojno odvisnih omrežnih plasti.
DP2: Identifikacija in klasifikacija faznih prehodov v koevolucijskih modelih, kjer so poleg strategij tudi interakcije med omrežji podvržene evoluciji. Želimo razumeti, kako se pojavi optimalna medsebojna odvisnost za koordinacijo med dvema omrežjema in katere so lastnosti, ki opredeljujejo optimalno interakcijo. Naš cilj je določiti merila perkolacije in razrede univerzalnosti na podlagi opazovanih rezultatov. Prav tako želimo pojasniti možnosti, povezane z razširitvijo te teorije na »multiplekse večplastnih omrežij«, kjer medsebojno deluje več večplastnih omrežij.
DP3: Identifikacija in klasifikacija faznih prehodov v koevolucijskih modelih, kjer interakcije med omrežji vplivajo na matriko izplačil in funkcijo koristnosti konkurenčnih igralcev. Cilj je temeljito razumeti, kako interakcije med omrežji vplivajo na sposobnost posameznih igralcev in kako razlike na mikro ravni vplivajo na makroskopsko stanje sistema. Pričakuje se, da bo ločitev časovnih skal med različnimi mikroskopskimi procesi, kot sta interakcija in posvojitev, ključni element, ki vpliva na makroskopsko opazne interakcije med različnimi plastmi omrežja. Temeljno vprašanje je, kako koevolucija takšne soodvisnosti vodi do pojava pristranskih koristnosti in kateri fazni prehodi so vključeni.
DP4: Posplošitev delovnih paketov 2 in 3 v smeri matematičnih modelov, ki jih zaznamujejo večtočkovne interakcije v nasprotju s parnimi interakcijami. Poudarek bo na kvalitativnih razlikah faznih prehodov, ki nastanejo kot posledica večtočkovnih interakcij. Javni razpis za sofinanciranje raziskovalnih projektov v letu 2020.
DP5: Karakterizacija faznih prehodov in prostorskih vzorcev, ki urejajo razvoj kazni v večplastnih omrežjih. Trenutne raziskave že poudarjajo nepopolnost obstoječega koncepta faznih prehodov, ki bi pojasnil vse fascinantne rezultate, in razumno je pričakovati, da bodo interakcije med omrežnimi plastmi le še povečale kompleksnost. Podrobno bomo obravnavali tudi razliko med kaznovanjem vrstnikov in institucionalnim sankcioniranjem ter tekmovanje med njima pri doseganju koordinacije.
DP6: Čeprav je nagrada poleg kazni le še ena manifestacija vzajemnosti v kontekstu koordinacije pri ljudeh, so lahko rezultati v izoliranem omrežju zelo različni. Temeljno vprašanje je, ali interakcije med omrežji zmanjšujejo ali krepijo te razlike in ali obstoječa klasifikacija faznih prehodov zadostuje za razlago vseh poti do koordinacije. Navsezadnje si bomo morda prizadevali razumeti vpliv korelirane nagrade in kazni v različnih omrežnih plasteh, pa tudi potencial institucionalizirane nagrade za usklajena dejanja.
DP7: Poleg nagrade in kazni želimo pojasniti tudi posledice bolj sofisticiranih strategij, kot je pogojna koordinacija, ter drugih neraziskanih vedenjskih tipov, ki sestavljajo družbeno vedenje v kompleksnih večplastnih omrežjih.
DP8: Eno od temeljnih odkritij, ki ga želimo podrobneje razložiti, je, da specifične interakcije agentov ne le prinesejo značilnih prostorskih vzorcev, temveč tudi, da nastajajoči prostorski vzorci posledično vplivajo na stabilnost možnih rešitev. Ta raziskava bi lahko bila še posebej pomembna za biološke sisteme, kjer se več strategij (ali vrst) poteguje za prostor in kjer konkurenco zato poganja zelo kompleksna prehranjevalna mreža, zato je koordinacija še posebej težko doseči.
DP9: Visoka relevantnost analize prostorskih vzorcev temelji na dejstvu, da lahko večtočkovne interakcije med agenti povzročijo neintuitivne in nepričakovane spremembe, ki vplivajo na hitrost invazije med širječimi se frontami ali celo popolnoma obrnejo pričakovano smer invazije. Pomembno je, da teh sprememb ni mogoče sklepati iz parnih primerjav konkurenčnih domen. Takšna prizadevanja bi lahko bila še posebej koristna, če ni neposrednih informacij o mikroskopskih interakcijah, kot je na primer v večini mikrobioloških
Bibliografske reference
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- Nowak, M. A. and Highfield, R. SuperCooperators: Altruism, Evolution, and Why We Need Each Other to Succeed. Free Press, New York, (2011).
- Perc, M. Phase transitions in models of human cooperation. Physics Letters A 380, 2803–2808 (2016).
- Perc, M. and Szolnoki, A. Coevolutionary games – a mini review. BioSystems 99, 109–125 (2010).
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- Szolnoki, A. and Perc, M. Correlation of positive and negative reciprocity fails to confer an evolutionary advantage: Phase transitions to elementary strategies. Phys. Rev. X 3, 041021 (2013).
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Projekt Fazni prehodi proti koordinaciji v večplastnih omrežjih, št. J1-2457 je sofinancirala Javna agencija za raziskovalno dejavnost Republike Slovenije iz državnega proračuna.
EN:
Coordination is the organization of different elements of a complex system so as to enable them to collective work together in an effective manner. As such, coordination encompasses a broad variety of different processes, including cooperation, synchronization, and pattern formation. Cooperation is the most important challenge to Darwin’s theory of evolution, and it is fundamental for the understanding of the main evolutionary transitions that led from single-cell organisms to complex animal and human societies. If only the fittest survive, why should an organism carry out an altruistic act that is costly to perform, but benefits another? Synchronization and pattern formation, on the other hand, are one of the most distinctive and universal phenomena across nonlinear sciences as well as in liquid crystals. Methods of nonequilibrium statistical physics, in particular the collective behaviour of interacting particles near phase transitions, have recently emerged as invaluable for understanding coordinating outcomes of complex systems in multilayer networks. Importantly, multi-point interactions that are involved in such processes give rise to critical behaviour that in complexity surpasses everything known from pairwise interactions that typically govern solid-state physics systems. The incompleteness of the existing theory is amplified further by the interactions among different networks, which give rise to multi-level dependencies that may induce cascading failures and accelerate sudden transitions towards system-wide catastrophes. Our aim is to utilize and extend the concept of phase transitions and universality, so that it will become apt for describing and explaining the emergence of coordination in multilayer networks. We will strive to develop widely applicable theoretical foundations that will open up new horizons towards understanding, predicting, and controlling a rich variety of fascinating phenomena that rely on coordination efforts. From large-scale cooperation in human societies to patterns in liquid-crystal films to science appreciation, the promise of having a firm theoretical grip on the phase transitions that lead to coordination in multilayer networks will have broad stimulating effects on research in theoretical and statistical physics.
Faze projekta in njihova realizacija
- WP1: We would like to understand how local topological features of interaction networks influence the emergence of coordination through the decisions of individual agents as they create and sever connections towards other members in the multilayer structure. Here we cancontinue onwards from our existing research efforts that have identified key coevolutionary processes that might facilitate cooperation and synchronization, as notable examples of coordination. The obvious goal is to extend this theory towards multilayer networks, where certain players are members in two or more different yet interdependent network layers.
- WP2: Identification and classification of phase transitions in coevolutionary models where besides strategies also the interactions between the networks are subject to evolution. We wish to understand how the optimal interdependence for coordination between two networks emerges, and what are the properties that define an optimal interaction. We aim to establish percolation criteria and universality classes based on the observed outcomes. We also aim to clarify the possibilities related to the extension of this theory to “multiplexes of multilayer networks” where several multilayer networks interact.
- WP3: Identification and classification of phase transitions in coevolutionary models where the interactions among networks influence the payoff matrix and the utility function of competing players. Here the goal is to understand thoroughly how the interactions between networks affect the fitness of individual players, and how the differences at the micro scale affect the macroscopic state of the system. The separation of times scales between different microscopic processes, like interaction and adoption, is expected to be a crucial element which influences the macroscopically observable interactions between different network layers. The fundamental question is how the coevolution of such an interdependence leads to the emergence of biased utilities, and which phase transitions are involved.
- WP4: A generalization of work packages 2 and 3 towards mathematical models that are haracterized by multi-point interactions, as opposed to pairwise interactions. The focus will Public call for co-financing of research projects in 2020 be on the qualitative differences of phase transitions that emerge as a consequence of multipoint interactions.
- WP5: Characterization of phase transitions and spatial patterns that govern the evolution of punishment in multilayer networks. Current research already highlights the incompleteness of the existing concept of phase transitions to account for all the fascinating results, and the reasonable expectation is that the interactions among network layers will only add further to the complexity. We shall also address in detail the difference between peer-based punishment efforts and institutional sanctioning, as well as the competition between the two in achieving coordination.
- WP6: Although reward is, besides punishment, just another manifestation of reciprocity in the context of coordination in humans, the outcomes on an isolated network can be very different. A fundamental question is whether interactions among networks diminish or amplify these differences, and whether the existing classification of phase transitions suffices to explain all the paths towards coordination. Ultimately, we may seek to understand the impact of correlated reward and punishment in different network layers, as well as the potentials of institutionalized reward for coordinated actions.
- WP7: In addition to reward and punishment, we also want to clarify the consequences of more sophisticated strategies, like conditional coordination as well as other unexplored behavioral types that constitute social behavior in complex multilayer networks.
- WP8: One of the fundamental discoveries on which we wish to elaborate on further is that specific interactions of agents do not simply yield characteristic spatial patterns, but also that the emerging spatial patterns in turn influence the stability of possible solutions. This research could be especially relevant for biological systems where several strategies (or species) compete for space, and where the competition is therefore driven by a highly complex food web, and where thus coordination is particularly difficult to achieve.
- WP9: The high relevance of the analysis of spatial patterns is rooted in the fact that multipoint interactions among agents may result in counterintuitive and unexpected changes that affect the invasion velocity between propagating fronts, or even altogether revert the expected direction of invasion. Importantly, these changes cannot be deduced from pairwise comparisons of competing domains. Such efforts could be particularly useful in the absence of direct information about the microscopic interactions, as is for example the case in the majority of microbiological systems. In these cases, the evaluation of emerging patterns could help to identify and resolve the main microscopic processes that drive coordination. This mayfind application in liquid crystals research too, where the exotic phases often yield multipoint interactions.
- WP10: Expanding the theory to related problems that go beyond coordination. Interacting networks are susceptible not only to the challenges of coordination, but also to the challenge of fairness, competition, and attack. The emergence of fairness is traditionally modeled with ultimatum bargaining. With methods of statistical physics, we aim to reveal hidden complexity in the pursuit of fair play in multilayer networks.
- WP11: We intend to explore the impact of different types of heterogeneities of payoff elements on the emergence of coordination. Heterogeneous payoff elements could be the consequence of many different effects. For example, the heterogeneity of resource availability may be due to permanently unequal or time-varying external conditions. Furthermore, it is reasonable to assume that the payoff elements depend also on the actual status of individual players. These considerations give rise to different types of heterogeneities, which are likely to introduce different phase transitions to coordination in multilayer networks.
The project “Phase transitions towards coordination in multilayer networks” (No. J1-2457) was co-financed by the Slovenian Research Agency from the state budget.