2 citations · 4 across the 11 of their papers we have counts for
13 papers
Epidemic Control using Stackelberg Mean Field Game with Budget Constraint
Huaning Liu, Gokce Dayanikli
Epidemic mitigation comes with a price in practice, and when budget is limited, its effective allocation becomes an important question on public policy. In this paper, we study epi…
Inverse Learning of the Altruism and Cost Level in Mixed-Individual Mean Field Games
Haoyang Cao, Gökçe Dayanıklı, Xiaofei Shi
Understanding how humans respond to incentives, both at the individual and collective levels, is crucial to the design of effective policies. Within the continuous-time stochastic…
Extended Graphon Mean-Field Games in Discrete Time
Hamed Amini, Zhongyuan Cao, Gökçe Dayanıklı +3
In this paper, we study games involving a continuum of heterogeneous players in the discrete-time setting with finite state spaces and continuous action spaces. We introduce a new…
Regulation of Rumor Propagation via (Multi-Leader) Stackelberg Graphon Games
Huaning Liu, Gokce Dayanikli
We study the control of rumor propagation in large networked populations by using Stackelberg graphon games. We first introduce a principal who wants to incentivize the spread of h…
Incorporating Authority Perception, Economic Status, and Behavioral Response in Infectious Disease Control
Huaning Liu, Junke Yang, Soren L. Larsen +2
We introduce a multi-population mean field game framework to examine how economic status and authority perception shape vaccination and social distancing decisions under different…
A Game-Theoretic Framework for Network Formation in Large Populations
Gokce Dayanikli, Mathieu Lauriere
In this paper, we study a model of network formation in large populations. Each agent can choose the strength of interaction (i.e. connection) with other agents to find a Nash equi…
Cooperation, Competition, and Common Pool Resources in Mean Field Games
Gokce Dayanikli, Mathieu Lauriere
Mean field games (MFGs) have been introduced to study Nash equilibria in very large population of self-interested agents. However, when applied to common pool resource (CPR) games,…
Modeling of Rumor Propagation in Large Populations with Network via Graphon Games
Huaning Liu, Gokce Dayanikli
In this paper, we propose a graphon game model to understand how rumor (such as fake news) propagates in large populations that are interacting on a network and how different polic…
How can the tragedy of the commons be prevented?: Introducing Linear Quadratic Mixed Mean Field Games
Gokce Dayanikli, Mathieu Lauriere
In a regular mean field game (MFG), the agents are assumed to be insignificant, they do not realize their effect on the population level and this may result in a phenomenon coined…
Machine Learning Methods for Large Population Games with Applications in Operations Research
Gokce Dayanikli, Mathieu Lauriere
In this tutorial, we provide an introduction to machine learning methods for finding Nash equilibria in games with large number of agents. These types of problems are important for…
From Nash Equilibrium to Social Optimum and vice versa: a Mean Field Perspective
Rene Carmona, Gokce Dayanikli, Francois Delarue +1
Mean field games (MFG) and mean field control (MFC) problems have been introduced to study large populations of strategic players. They correspond respectively to non-cooperative o…
Multi-population Mean Field Games with Multiple Major Players: Application to Carbon Emission Regulations
Gokce Dayanikli, Mathieu Lauriere
In this paper, we propose and study a mean field game model with multiple populations of minor players and multiple major players, motivated by applications to the regulation of ca…
Deep Learning for Population-Dependent Controls in Mean Field Control Problems with Common Noise
Gokce Dayanikli, Mathieu Lauriere, Jiacheng Zhang
In this paper, we propose several approaches to learn the optimal population-dependent controls in order to solve mean field control problems (MFC). Such policies enable us to solv…