Ph. D. Project
"Individual and Collective Decarbonization Strategies: An Approach at the Interface of Game Theory and Neuroscience."
2023/09/14 - 2026/09/13
Other supervisor(s):
VARMA Vineeth (
The state of the art on decarbonization strategies by microscopic entities such as individuals and the mechanisms of incentivizing individuals to follow a global decarbonization plan are highly incomplete in formal terms. As a result, proposed decarbonization strategies are typically suboptimal in terms of a given global performance metric for the incentivizing entity and do not gain the adherence of the actors involved in decarbonization. To address this problem, one of the objectives of this thesis is to make significant advancements in modeling a group of CO2-emitting individuals who are influenced both by other individuals through a social network and by an external incentivizing or regulatory entity (e.g., a government). To achieve this, we will leverage and develop the most recent findings in neuroscience and the expertise of CRAN to propose a realistic behavioral model of individuals regarding decarbonization. We will construct a graph model of the social network that characterizes the mutual influence among emitting individuals and integrates the developed individual behavioral model. We will design decarbonization strategies and incentivization mechanisms that ensure strategic stability properties (and thus individual adherence) and leverage the dynamic attributes of the social network graph. The synergy of game theory, dynamical systems, and neuroscience provides a promising new perspective to achieve the goals of this project.
Decarbonization, Game theory, Optimization, Machine learning, Neuroscience
Control Identification Diagnosis