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A label-state formulation of stochastic graphon games and approximate equilibria on large networks
This paper studies stochastic games on large graphs and their graphon limits. We propose a
new formulation of graphon games based on a single typical player's label-state distribution …
new formulation of graphon games based on a single typical player's label-state distribution …
Tracking-based distributed equilibrium seeking for aggregative games
We propose fully distributed algorithms for Nash equilibrium seeking in aggregative games
over networks. We first consider the case where local constraints are present and we design …
over networks. We first consider the case where local constraints are present and we design …
Collective intelligence as a public good
We discuss measures of collective intelligence in evolved and designed self-organizing
ensembles, defining collective intelligence in terms of the benefits to be gained through the …
ensembles, defining collective intelligence in terms of the benefits to be gained through the …
Gamekeeper: Online learning for admission control of networked open multiagent systems
We consider open games where players arrive according to a Poisson process with rate and
stay in the game for an exponential random duration with rate. The game evolves in …
stay in the game for an exponential random duration with rate. The game evolves in …
Quantifying leadership in climate negotiations: A social power game
We consider complex multistage multiagent negotiation processes such as those occurring
at climate conferences and ask ourselves how can an agent maximize its social power …
at climate conferences and ask ourselves how can an agent maximize its social power …
Big hype: Best intervention in games via distributed hypergradient descent
Hierarchical decision making problems, such as bilevel programs and Stackelberg games,
are attracting increasing interest in both the engineering and machine learning communities …
are attracting increasing interest in both the engineering and machine learning communities …
Learning the optimal control for evolving systems with converging dynamics
We consider a principle or controller that can pick actions from a fixed action set to control an
evolving system with converging dynamics. The actions are interpreted as different …
evolving system with converging dynamics. The actions are interpreted as different …
Learning in potential games for electric power grids: Models, dynamics, and outlook
Noncooperative game-theoretic methods have been widely utilized in system-level
engineering applications as they are capable of aggregating interests, information, and …
engineering applications as they are capable of aggregating interests, information, and …
A Distributed Feedback-based Framework for Nonlinear Aggregative Optimal Control
In this paper, we propose a distributed, first-order, feedback-based approach to solve
nonlinear optimal control problems with aggregative cost functions over networks of …
nonlinear optimal control problems with aggregative cost functions over networks of …
Persuasion, news sharing, and cascades on social networks
We study a model of online news dissemination on a Twitter-like social network. Given a
news item and its credibility, agents with heterogeneous priors strategically decide whether …
news item and its credibility, agents with heterogeneous priors strategically decide whether …