MOCENNI CHIARA

Presentazione

Chiara Mocenni is associate professor of Systems and Control at the Department of Information Engineering and Mathematics (DIISM) of the University of Siena, where she teaches Game Theory and Complex Dynamic Systems in the Courses of Artificial Intelligence and Automation, Applied Mathematics and Engineering Management.

CM received her Laurea Degree in Mathematics from the University of Siena in 1992's. Before joining the Systems and Control Group at DIISM in 1998 as Research Associate, she received the PhD in Physical Chemistry defending a thesis on mathematical modeling of ecological systems.

From its activation in 2000, CM has been fellow of the Center for the Study of Complex Systems of the University of Siena and served on its Board of Directors. She also founded the Complex Systems Community, a network of researchers working in the field of complex systems.

From 2013 to 2016 Chiara Mocenni has been Special Visiting Researcher at Instituto Nacional de Matematica Pura e Aplicada (IMPA) of Rio de Janeiro, Brazil. The research developed at IMPA concerned Evolutionary Games on Networks for Modeling Complex Biological and Socio-Economic Phenomena.

Main research interests are: Complex Systems, Cooperative Dynamics on Networks, , Evolutionary Games on Networks, Mathematical Modeling and Identification of Biological and Social Systems, Nonlinear dynamics and Bifurcations.

Orari di ricevimento

  • Giovedi' dalle 11:00 alle 13:00
    Luogo: Edificio S. Niccolo', Via Roma n.56 - room 232

Anyway, students can come to my office at any time.

Attività didattica

Complex Dynamic Systems

The course presents an introduction to the theory of nonlinear dynamic systems, including bifurcation theory and qualitative analysis of nonlinear ordinary differential equations. Algorithms for the simulation of complex dynamics, such as limit cycle oscillations and chaotic behavior are presented. Several examples of complex systems in discrete and continuous time are tackled, with application to population dynamics, economic, ecological and biological systems. 

 

Game Theory

The course is aimed at introducing the methodological bases of game theory and evolutionary game theory. In the first part of the course, the concept of game is introduced as the strategic decision of a player. The game outcome depends on the choices of other players which share the same information. In the second part of the course, the evolutionary game theory is introduced. In this case the game is repeated in a large population of players. The ensemble of the decisions will affect the future distribution of strategies inside the population. Finally, the course provides several examples and applications in socio-economic, environmental and engineering fields. 

 

ANNO ACCADEMICO DI ESPLETAMENTO: 2021/2022

Anno di corso: 2 Corso di Laurea Magistrale APPLIED MATHEMATICS - MATEMATICA APPLICATA A.A. 2020/2021
Anno di corso: 2 Corso di Laurea Magistrale APPLIED MATHEMATICS - MATEMATICA APPLICATA A.A. 2020/2021

ANNO ACCADEMICO DI ESPLETAMENTO: 2020/2021

Anno di corso: 2 Corso di Laurea Magistrale APPLIED MATHEMATICS - MATEMATICA APPLICATA A.A. 2019/2020
Anno di corso: 2 Corso di Laurea Magistrale APPLIED MATHEMATICS - MATEMATICA APPLICATA A.A. 2019/2020

ANNO ACCADEMICO DI ESPLETAMENTO: 2019/2020

Anno di corso: 2 Corso di Laurea Magistrale APPLIED MATHEMATICS - MATEMATICA APPLICATA A.A. 2018/2019
Anno di corso: 1 Corso di Laurea Magistrale ENGINEERING MANAGEMENT A.A. 2019/2020

ANNO ACCADEMICO DI ESPLETAMENTO: 2018/2019

Anno di corso: 2 Corso di Laurea Magistrale APPLIED MATHEMATICS - MATEMATICA APPLICATA A.A. 2017/2018
Anno di corso: 1 Corso di Laurea Magistrale ENGINEERING MANAGEMENT A.A. 2018/2019

ANNO ACCADEMICO DI ESPLETAMENTO: 2017/2018

Anno di corso: 1 Corso di Laurea Magistrale ENGINEERING MANAGEMENT A.A. 2017/2018
Anno di corso: 1 Corso di Laurea Magistrale ENGINEERING MANAGEMENT A.A. 2017/2018

Attività di ricerca

Evolutionary Games on Networks

Development of mathematical models, grounded on evolutionary game equations, where players are located at the nodes of a network of connections. The models describe decision mechanisms of a finite set of players under replication, selection pressure and social influence. An extended version of the model describes the continuous dynamics of individuals or groups interacting each other under a baseline prisoner's dilemma game appropriately modified with the aim of accounting for a self-regulative inertial factor which favours the onset of cooperation. The extended model well explains propensity to cooperation in European Countries under the assumption that individuals are driven by homophily, endogamy and civicness and shows formally that strong cooperation within familistic cliques induces a decrease of cooperation at global level. 

The model has been also applied to investigate the formation of networks among the members of a microbial population as a response to hostile environments. A further application to neuroscience showed a good performance of the evolutionary game equations on networks in reproducing spontaneous brain behavior.

Madeo D., Mocenni C., "How cooperation helps Epidemic Containment", Games, submitted 2021

Madeo D., Salvatore S., Mannarini T., Mocenni C., "Modeling pluralism and self-regulation explains the emergence of cooperation in networked societies", Sci. Rep. 2021

Madeo D., Mocenni C., "Consensus towards Partially Cooperative Strategies in Self-Regulated Evolutionary Games on Networks", Games 2021

Madeo D., Mocenni C., "Self-regulation versus social influence for promoting cooperation on networks", Sci. Rep. 2020

Madeo D., Talarico A.,Pascual-Leone A., Mocenni C., Santarnecchi E., "An evolutionary game theory model of spontaneous brain functioning", Sci. Rep. 2017

Iacobelli G., Madeo, D., Mocenni C., "Lumping evolutionary game dynamics on networks", J. Theor. Biol. 2016

Madeo D. & Mocenni C., "Game Interactions and Dynamics on Networked Populations" IEEE Trans. Aut. Control, 2015

Biophysical Systems Analysis and Behavior

In the field of monitoring and analysing the environmental status of water systems, we have developed tools for decision support and real-time water monitoring based on low cost unmanned surface vehicles and mathematical modeling.

Madeo D., Pozzebon A., Mocenni, C., & Bertoni D., "A Low-Cost Unmanned Surface Vehicle for Pervasive Water Quality Monitoring", IEEE Trans. Instr. and Meas., 2020

Casini M., Mocenni C., Paoletti S., & Pranzo M., "Decision support system development for integrated management of European coastal lagoons", Env. Mod. & Soft., 2015

A physical model for the characterization of magnetic hydrogels subject to external magnetic fields has been introduced and validated. 

Madeo D., Bevilacqua G., Biancalana V., Dancheva Y., Mocenni, C., "A physical model for the characterization of magnetic hydrogels subject to external magnetic fields", J. Magn. & Magn. Mat., 2020

A bounded rationality model of spontaneous remission from addctive behavioral patterns has been designed. We showed that natural recovery from addiction without external committments is feasible by assuming enough high level of awareness of individuals.

Mocenni C., Tiezzi S., Montefrancesco G., "A Model of Spontaneous Remission from Addiction", J. Appl. Behav. Econ., 2019

Nonlinear time series analysis

Nonlinear time series analysis has been applied to the study of brain patterns with particular attention to the level of hypnotizability of subjects. The research has been conducted by analyzing the EEG time series recorded in several regions of the scalpo of resting state, not hypnotized subjects.

Madeo D., Caastellani E., Mocenni C., Santarcangelo E., "Pain perception and EEG dynamics: does hypnotizability account for the efficacy of the suggestions of analgesia?", Physiol. & Behav., 2015

Application of nonlinear time series analysis to the reconstruction of embedded state spaces and detection of critical regimes in complex systems. The methodology allowed the identification of structurally different regimes, e.g. stable and unstable spiral waves, in the Complex Ginzburg-Landau equation and in biochemical reaction-diffusion systems undergoing Turing instabilities and in presence of roughness in the boundaries.

Mocenni C., Sparacino E., & J. P. Z., "Effective rough boundary parametrization for reaction-diffusion systems", Appl. An. Discr. Math., 2014

Facchini A., & Mocenni C., "Recurrence methods for the identification of morphogenetic patterns", Plos ONE, 2013

Mocenni C., Facchini A., & Vicino A., "Identifying the dynamics of complex spatio-temporal systems by spatial recurrence properties", PNAS, 2010 

Pubblicazioni in evidenza:

  • Madeo, D., Salvatore, S., Mannarini, T., & Mocenni, C. (2021). Modeling pluralism and self-regulation explains the emergence of cooperation in networked societies. SCIENTIFIC REPORTS, 11(1) [10.1038/s41598-021-98524-5]. - dettaglio
  • Madeo, D., & Mocenni, C. (2021). Consensus towards Partially Cooperative Strategies in Self-Regulated Evolutionary Games on Networks. GAMES, 12(3) [10.3390/g12030060]. - dettaglio
  • Madeo, D., & Mocenni, C. (2020). Self-regulation versus social influence for promoting cooperation on networks. SCIENTIFIC REPORTS, 10 [10.1038/s41598-020-61634-7]. - dettaglio
  • Madeo, D., Pozzebon, A., Mocenni, C., & Bertoni, D. (2020). A Low-Cost Unmanned Surface Vehicle for Pervasive Water Quality Monitoring. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 69(4), 1433-1444 [10.1109/TIM.2019.2963515]. - dettaglio
  • Madeo, D., Mocenni, C., Moraes, J.C., & Zubelli, J.P. (2019). The role of self-loops and link removal in evolutionary games on networks. MATHEMATICAL BIOSCIENCES AND ENGINEERING, 16(5), 5287-5306. - dettaglio