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Found 9 papers, 0 papers with code
Social herding in mean field games
In this paper, we consider a mean field model of social behavior where there are an infinite number of players, each of whom observes a type privately that represents her preference, and publicly observes a mean field state of types and actions of the players in the society.
Mean field teams and games with correlated types
In this paper, we introduce a new model of mean field teams and games with \emph{correlated types} where there are a large population of homogeneous players sequentially making strategic decisions and each player is affected by other players through an aggregate population state.
Master equation of discrete-time Stackelberg mean field games with multiple leaders
In this paper, we consider a discrete-time Stackelberg graphon mean field game with a finite number of leaders, a finite number of major followers and an infinite number of minor followers.
Master Equation for Discrete-Time Stackelberg Mean Field Games with single leader
First, we consider an epidemic model where the followers get infected based on the mean field population.
Convergence of Generalized Belief Propagation Algorithm on Graphs with Motifs
Belief propagation is a fundamental message-passing algorithm for numerous applications in machine learning.
Multi-Agent Decentralized Belief Propagation on Graphs
We consider the problem of interactive partially observable Markov decision processes (I-POMDPs), where the agents are located at the nodes of a communication network.
Model-free Reinforcement Learning for Stochastic Stackelberg Security Games
In such a scenario, the leader has the advantage of committing to a policy which maximizes its own returns given the knowledge that the follower is going to play the best response to its policy.
Fault Tolerant Equilibria in Anonymous Games: best response correspondences and fixed points
A Nash equilibrium in a game with $N$ players is said to be $\alpha$-tolerant if no non-faulty user wants to deviate from an equilibrium strategy as long as $N-\alpha-1$ other players are playing the equilibrium strategies, i. e., it is robust to deviations from rationality by $\alpha$ faulty players.
Mechanism Design for Large Scale Network Utility Maximization
With infinitely many agents, agents' truthful reports of their types are their dominant strategies; for the finite case, each agent's incentive to misreport converges quadratically to zero.
Distributed Optimization
Computer Science and Game Theory
Theoretical Economics
