International Society on Dynamic Games

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January 25, 2021

ISS Informal Systems Seminar

Jan 29, 2021 02:00 PM – 03:00 PM (Montreal time)

LQG mean field games with a major agent: Nash certainty equivalence versus probabilistic approach

Dena Firoozi – Department of Decision Sciences, HEC Montréal, Canada

 

 

Webinar link

Webinar ID: 910 7928 6959

Passcode: VISS

Mean field game systems consisting of a major agent and a large population of minor agents were introduced in (Huang, 2010) in an LQG setup. In the past years several approaches towards major-minor mean field games have been developed, principally (i) the Nash certainty equivalence (Huang, 2010), (ii) master equations, (iii) asymptotic solvability, and (iv) the probabilistic approach. In a recent work (Huang, 2020), for the LQG case the equivalence of the solutions obtained via approaches (i)-(iii) was established. In this talk we first review approaches (i) and (iv). We then demonstrate that the closed-loop Nash equilibrium derived in the infinite-population limit through (i) and (iv) are identical.

Published by Sergey Kumkov
January 25, 2021

Dynamic Games and Applications Seminar

Chair in Game Theory and Management

GERAD

Jan 28, 2021 11:00 AM – 12:00 PM (Montreal time)

Fuzzy fractional-order model of the novel coronavirus: The impact of delay strategies on the pandemic dynamics model with nonlinear incidence rate

Massimiliano Ferrara – Mediterranea University of Reggio Calabria, Italy

 

Webinar link

Meeting ID: 962 7774 9870

Pass code: 285404

 

In this paper, a novel coronavirus infection system with a fuzzy fractional differential equation defined in Caputo’s sense is developed. By using the fuzzy Laplace method coupled with Adomian decomposition transform, numerical results are obtained for better understanding of the dynamical structures of the physical behavior of COVID-19. Such behavior on the general properties of RNA in COVID-19 is also investigated for the governing model. Due to non-availability of the vaccination, delay strategies such as social distancing, travel restrictions, extension in holidays, use of facemask, and self- quarantine are the effective treatment to control the pandemic of coronavirus. So, we proposed the delayed susceptible-exposed- infected-recovered model with nonlinear incidence rate to study the effective role of delay strategies. For this analysis, we discussed three types of equilibria of the model such as trivial, coronavirus free and coronavirus existence with delay term. The local and global stabilities are investigated by using well-posed notation, Routh Hurwitz criterion, Lyapunov function, and Lasalle invariance principle. 

Published by Sergey Kumkov
January 18, 2021

 

ISS Informal Systems Seminar

Jan 22, 10:00 AM – 11:00 AM (Montreal time)

Mean-field games models of price formation

Joao Saude – JP Morgan AI Research, United States

 

Joao Saude

Webinar link
Webinar link: 910 7928 6959
Passcode: VISS

We consider dynamical systems with a large number of agents that can store and trade a commodity such as electricity. We present a price-formation model consisting of constrained mean-field games where the price is a Lagrange multiplier for the supply vs. demand balance condition. We illustrate the model using real data of daily energy consumption in the UK. Then we present a Fourier approximation method for the solutions of first-order nonlocal mean-field games. We approximate the system by a simpler one that is equivalent to a convex optimization problem over a finite-dimensional subspace of continuous curves. Time permitting, we discuss possible applications to price formation problems where prices depend on state and time.

Published by Sergey Kumkov
January 18, 2021

Dynamic Games and Applications Seminar

Jan 21, 11:00 AM – 12:00 PM (Montreal time)

Control of an epidemic with endogenous treatment capability under popular discontent and social fatigue

Fouad El Ouardighi – ESSEC Business School, France

Fouad El Ouardighi

 

Webinar link
Meeting ID: 962 7774 9870
Passcode: 285404

The primary issue in this paper is to determine whether mobility restrictions or securing social interactions is most effective in countering an epidemic disease that spreads also via asymptomatic transmission. We develop an optimal control policy model wherein i) treatment capabilities are endogenous, ii) the social loss due to disease-related deaths is part of the tradeoff in terms of health and social welfare perspectives, iii) the policymaker's inability to counter the disease gives rise to growing popular discontent over time, and iv) nontherapeutic intervention policy engenders social fatigue over time. We also allow for partial immunity upon recovery. In many ways, our model applies to the recent pandemic caused by the SARS-Cov-2 virus. In this setup, we identify which non-therapeutic policy option between mobility restrictions or securing social interactions most effectively minimizes both the impact of policymaker’s inability and the ensuing popular discontent and social fatigue.

Published by Sergey Kumkov
January 11, 2021

ISS Informal Systems Seminar

Jan 15, 02:00 PM – 03:00 PM (Montreal time)

 

Social learning under behavioral assumptions

Rabih Salhab – Institute for Data, Systems, and Society, MIT, United States

Rabih Salhab

Webinar link

Webinar ID: 910 7928 6959

Passcode: VISS

I will present two recent works on social learning under behavioral assumptions. The first is Social Learning with Sparse Belief Samples. In this work, we introduce a non-Bayesian model of learning over a social network where a group of agents with insufficient and heterogeneous sources of information share their experiences to learn an underlying state of the world. Inspired by a recent body of research in cognitive science on human decision making, we presume two behavioral assumptions. Motivated by the coarseness of communication, our first assumption posits that agents only share samples taken from their belief distribution over the set of states, to which we refer as their actions. This situation is to be contrasted with that of sharing the full belief, i.e. probability distribution over the entire set of states. The second assumption is limited cognitive power, based on which individuals incorporate their neighbors’ actions into their beliefs following a simple DeGroot-like social learning rule which suffers from redundancy neglect and imperfect recall of the past history. We show that so long as all the individuals trust their neighbors’ actions more than their private signals, they may end up mislearning the state with positive probability. Learning, on the other hand, requires that the population includes a group of self-confident experts in different states. This means that for each state, there is an agent whose signaling function for her state of expertise is distinguishable from the convex hull of the remaining signaling functions, and that her private signals sufficiently weigh in her social learning rule. This is a joint work with Amir Ajorlou and Ali Jadbabaie.

The second work is Social Learning with Unreliable Agents and Self-reinforcing Stochastic Dynamics. We consider a group of agents that have fixed unobservable binary ``beliefs’’. An individual’s belief models for example their political support (Democrat or Republican). At each time period, agents broadcast binary opinions on a social network. We assume that individuals may lie and declare opinions different from their true beliefs to conform with their neighbors. This raises the natural question as to whether one can estimate the agents’ true beliefs from observations of declared opinions. We analyze this question in the special case of complete graph. We show that, as long as the population does not include large majorities, estimation of aggregate true belief and individual true beliefs is possible. On the other hand, large majorities force minorities to lie as time goes to infinity, which makes asymptotic estimation impossible. This is a joint work with Anuran Makur, Ali Jadbabaie, and Elchanan Mossel.

Published by Sergey Kumkov
January 11, 2021

Dynamic Games and Applications Seminar

Jan 14, 11:00 AM – 12:00 PM (Montreal time)

All symmetric equilibria in differential games with public goods

Florian Wagener – University of Amsterdam, Netherlands

Seminar link

Meeting ID: 962 7774 9870

Passcode: 285404

 

We characterise the entire set of symmetric stationary Markov-perfect Nash equilibria (MPE) in a class of differential games of public good investment, using the canonical problem of climate change as an example. We provide a sufficient and necessary condition for MPE and show how the set of MPE is constructed. The equilibrium in continuous strategies, unique in our context, is Pareto-dominated by any other equilibrium. We extend the theory of differential games to deal with payoffs under discontinuous strategies. Our methods work under general functional forms.

Published by Sergey Kumkov
December 16, 2020

Dear Colleagues,

despite of COVID-19, some scientific activities are planned for the next year. Information on some of them is appeared in the sectiion Related Meetings

Published by Sergey Kumkov
December 15, 2020

15 open positions for Early Stage Reserchers within the The Marie Skłodowska-Curie European Training Network – EvoGamesPlus (Evolutionary games and population dynamics: from theory to applications)

The Marie Skłodowska-Curie European Training Network – EvoGamesPlus (Evolutionary games and population dynamics: from theory to applications) invites applications for 15 early-stage researcher (ESR) / PhD positions, available with a starting date in the period July 2021 - September 2021. The appointments will be on a full-time, fixed term employment contract basis for a duration of 36 months.  

List of available ESR positions (+ host institutions & supervisors):

ESR 1: The evolution of cooperation in structured populations involving multiplayer interactions (City, University of London, Department of Mathematics, United Kingdom). Supervisors: Prof. Mark Broom (Mark.Broom.1@city.ac.uk) and Dr. Andrea Baronchelli

ESR2: Eco-evolutionary dynamics of complex multiplayer and multiple games (Max Planck Institute for Evolutionary Biology, Department of Evolutionary Theory, Germany). Supervisors: Dr. Chatainya S. Gokhale (gokhale@evolbio.mpg.de) and Prof. Arne Traulsen

ESR3: The evolution of cooperation in structured populations involving multi-level selection (Centre for Ecological Research, Institute of Evolution, Hungary). Supervisors: Dr. Ádám Kun (kunadam@elte.hu) and Dr. József Garay

ESR4: Criticality and self-organization of evolutionary game (Delft University of Technology, Delft Institute of Applied Mathematics, The Netherlands). Supervisors: Dr. Johan Dubbeldam (J.L.A.Dubbeldam@tudelft.nl) and Dr. Wim van Horssen

ESR5: Critical Transitions in Evolutionary Games (University College Cork, School of Mathematical Sciences, Ireland). Supervisors: Prof. Sebastian Wieczorek (sebastian.wieczorek@ucc.ie) and Dr. Kieran Mulchrone

ESR6: The evolution of cooperation in populations involving multi-player games and time delays (University of Warsaw, Institute of Applied Mathematics and Mechanics, Poland). Supervisors: Prof. Jacek Miękisz (miekisz@mimuw.edu.pl) and Prof. Marek Bodnar

ESR7: Information theoretic aspects of modularity, self-similarity, and stability in multiplayer games on adaptive networks (Medical University of Vienna, Section for Science of Complex Systems, Austria). Supervisors: Dr. Rudolf Hanel (rudolf.hanel@meduniwien.ac.at) and Dr. Peter Klimek

ESR8: Theory of Stackelberg evolutionary games for cancer treatment. (Maastricht University, Department of Data Science & Knowledge Engineering, Dynamic Game Theory, The Netherlands). Supervisors: Dr. Kateřina Staňková (k.stankova@maastrichtuniversity.nl)  and Dr. Rachel Cavill

ESR9: Impact of different resistance mechanisms on the outcomes of cancer treatment game (Queen Mary University of London, School of Mathematical Sciences, United Kingdom). Supervisors: Dr. Weini Huang (weini.huang@qmul.ac.uk) and Dr. Dudley Stark

ESR10: Evolutionary therapy in ovarian cancer (Queen Mary University of London, Barts Cancer Institute, United Kingdom). Supervisors: Dr. Benjamin Werner (b.werner@qmul.ac.uk) and Prof. Trevor Graham

ESR11: Data-driven support to understanding of complex dynamical physical phenomena, such as epidemics (University of Torino, Department of Computer Science, Italy). Supervisors: Prof. Maria Luisa Sapino (mlsapino@di.unito.it) and Prof. Matteo Sereno

ESR12: Models of evolution in network-structured populations (University of Liverpool, Department of Mathematical Sciences, United Kingdom). Supervisors: Dr. Kieran Sharkey (K.J.Sharkey@liverpool.ac.uk) and Dr. Kate Baker

ESR13: Waning of immunity due to pathogen evolution (University of Szeged, Bolyai Institute, Hungary). Supervisors: Dr. Gergely Röst (rost@math.u-szeged.hu) and Dr. Tibor Krisztin

ESR14: Models of eco-evolutionary dynamics of population interaction networks (University of South Bohemia, Department of Mathematics, Czech Republic). Supervisors: Prof. Vlastimil Krivan (vlastimil.krivan@gmail.com) and Dr. Luděk Berec

ESR15: Node embedding for epidemic spreading processes on temporal networks (ISI Foundation, Department of Digital Epidemiology, Italy). Supervisors: Dr. Daniela Paolotti (daniela.paolotti@isi.it), Dr. Michele Tizzoni and Prof. Ciro Cattuto

For more details and how to apply visit the EvoGamesPlus webpage.

Published by Katerina Stankova
December 9, 2020

ISS Informal Systems Seminar

Friday, December 11, 11:00 AM – 12:00 PM (Montreal time)

Subspace decompositions in graphon control and graphon mean field games

Shuang Gao – Department of Electrical and Computer Engineering, McGill University, Canada

Webinar link
Meeting ID: 910 7928 6959
Pass code: VISS

Graphon control (CDC 17-18-19, IEEE TAC 20, Gao and Caines) and graphon mean field games (CDC18, CDC19, Caines and Huang) were used to address decision problems on very large-scale networks by employing graphons to represent arbitrary size graphs, from, respectively centralized and decentralized perspectives. Graphon couplings may appear in states, controls and cost, and may be represented by different graphons in each case. In this talk, I will first briefly introduce graphon theory. Then I will present the use of subspace decompositions in graphon control and graphon mean field games in a linear quadratic setting. The complexity of the methods corresponds to that of the solution of one nd × nd dimensional Riccati equation and one n × n Riccati equation, where n is the dimension of each nodal agent state and d is the dimension of the (nontrivial) invariant subspace shared by the coupling operators. Applications to the regulation of harmonic oscillators coupled over networks with uncertainties will be demonstrated (IEEE TCNS (Submitted), Gao and Caines).

Published by Sergey Kumkov
December 9, 2020

Online Seminars on Dynamic Games and Applications

 Chair in Game Theory and ManagementGERAD

Thursday, December 10, 11:00 AM – 12:00 PM (Montreal time)

Supplier development in a multi-tier supply chain

Ozgen Karaer – Middle East Technical University, Turkey

Webinar link
Meeting ID: 962 7774 9870
Pass code: 285404

We examine how a buyer can use a full-control strategy and cost sharing to develop the sustainable quality capabilities of his tier-1 and tier-2 suppliers. In particular, we consider how the buyer’s development decisions and the suppliers’ sustainable quality decisions are impacted by consumers’ demand sensitivity to sustainable quality and the division of the supply chain margin. Two quality-demand models are studied – the overall quality of the supply chain equals either (i) the sum of or (ii) the minimum between the suppliers’ quality levels. We find that when the suppliers’ sustainable quality levels are additive, even if the low-margin supplier has a positive net profit return from improved quality, she may still choose to free ride on the high-margin supplier’s quality investment. Interestingly, the buyer can cause the free riding with his cost-sharing decisions. When instead, the overall sustainable quality is determined by the minimum between the suppliers’ quality levels, the buyer’s strategy is often to focus only on developing the low-margin supplier. Nevertheless, when the buyer’s market gain from improved quality is large and the suppliers’ gains are comparable to one another, the buyer can justify sharing costs with both suppliers and raising the overall sustainable quality of the supply chain to a level neither supplier can achieve without development support. Joint work with Tim Kraft and Pinar Yalcin.

Published by Sergey Kumkov
December 4, 2020
Dynamic Games and Applications
Call for Papers

Special Issue on Dynamic Games for Modeling and Control of Epidemics


Guest Editors:

Quanyan Zhu, New York University, qz494@nyu.edu
Elena Gubar, Saint-Petersburg State University, e.gubar@spbu.ru
Eitan Altman, INRIA, Sophia-Antipolis, eitan.altman@inria.fr


The recent COVID-19 pandemic has caused a significant social and economic disruption in today’s connected world. There is an imminent need to understand and control the spreading of the disease over networks. Dynamic games provide a natural framework to model and analyze the individual incentives and their social interactions over large networks. Sophisticated models such as evolutionary games and mean-field games have enabled the understanding of the emerging population-level phenomena and effective control mechanisms. Connecting dynamic games and epidemic models offers a scientific foundation for rigorous and quantitative analysis and design of screening, containment, and mitigation strategies for large-scale dynamic and network systems. This cross-disciplinary approach will not only address the current challenges with COVID-19 but also shed light on related problems of computer viruses and misinformation in networks. In 2021, Dynamic Games and Applications will publish a special issue on the subject, emphasizing new game-theoretic models and rigorous analysis approaches for epidemics and network systems. The special issue welcomes submissions from theoreticians as well as applied researchers, and it is important to note that papers submitted should have epidemics as the centerpiece. Within that framework, some selected topics (among others) of special interest are:

•	Evolutionary games for epidemic modeling
•	Integration of game theory and mathematical modelling of infectious disease
•	Differential games for decentralized control of epidemics
•	Design of treatment, vaccination, and quarantining strategies
•	Mean-field game approach to epidemic control 
•	Multi-agent reinforcement learning methods for epidemics
•	Epidemic model-order reduction and identification
•	Coupled information and disease spreading
•	Competitive virus spreading
•	Cooperative control of epidemic models
•	Empirical and experimental studies
•	Applications of epidemic modeling and games to communication networks, social networks, biological networks, etc.

Submission Deadline: April 15, 2021

Publication Date: December 2021

We encourage early submissions, and the submissions will be processed as soon as they are received. Papers that still require major revision after the second round will not be accepted for the special issue and will be treated as submissions to a regular issue. The accepted papers will appear online in advance of the production of the full special issue.

For submission instructions, please visit:

http://www.springer.com/mathematics/applications/journal/13235
Published by Sergey Kumkov
December 2, 2020

Online Seminars on Dynamic Games and Applications

Thursday, December 3, 11:00 AM – 12:00 PM (Montreal time)

Dynamic games for cyber deception

Quanyan Zhu – New York University, United States

Webinar link
Meeting ID: 962 7774 9870
Pass code: 285404

Deception and anti-deception technologies are new paradigms of active cyber defense. They provide defenders a proactive and autonomous security mechanism by engaging the adversaries and influencing their moves to the defender’s advantage. Game theory captures the strategic and self-interested nature of attackers and defenders in cybersecurity. It provides an ideal set of quantitative tools to develop such a framework to analyze and design deception. In this talk, we first present a taxonomy of deception and counter-deception and understand how they can be conceptualized, quantified, and designed or mitigated. Then, we present a class of dynamic games of incomplete information to capture the fundamental characteristics of deception and demonstrate the applications of game theory and learning in problems such as attack engagement, lateral movement, and information manipulation. The talk will also discuss open problems and research challenges that the game theory community can address and contribute with an objective to build a multidisciplinary bridge between game theory and cybersecurity.

 

Published by Sergey Kumkov
November 25, 2020

 

Online Seminars on Dynamic Games and Applications

Thursday, November 26, 11:00 AM – 12:00 PM (Montreal time)

Winning strategy for pursuers in pursuit-evasion differential games

Mehdi Salimi – McMaster University, Canada

Webinar link
Meeting ID: 962 7774 9870
Pass code: 285404

In this presentation, we review one classical problem in the subject of pursuit evasion games which is called the lion and man game. Then we study a pursuit evasion differential game in plane. Controls of pursuer and evader satisfy on the integral or geometric constraint. We define a winning strategy for the pursuer and show that using this strategy the pursuer can catch the evader.

 

 

Published by Sergey Kumkov