3 citations · 9 across the 22 of their papers we have counts for
12 papers · 1 filter
Network Design for Social Welfare
Abhishek Shende, Deepanshu Vasal, Sriram Vishwanath
In this paper, we consider the problem of network design on network games. We study the conditions on the adjacency matrix of the underlying network to design a game such that the…
Multi-Agent Decentralized Belief Propagation on Graphs
Yitao Chen, Deepanshu Vasal
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. Specifically…
Existence of structured perfect Bayesian equilibrium in dynamic games of asymmetric information
Deepanshu Vasal
In~[1],authors considered a general finite horizon model of dynamic game of asymmetric information, where N players have types evolving as independent Markovian process, where each…
Model-free Reinforcement Learning for Stochastic Stackelberg Security Games
Rajesh K Mishra, Deepanshu Vasal, Sriram Vishwanath
In this paper, we consider a sequential stochastic Stackelberg game with two players, a leader and a follower. The follower has access to the state of the system while the leader d…
Dynamic information design
Deepanshu Vasal
We consider the problem of dynamic information design with one sender and one receiver where the sender observers a private state of the system and takes an action to send a signal…
Fault Tolerant Equilibria in Anonymous Games: best response correspondences and fixed points
Deepanshu Vasal, Randall Berry
The notion of fault tolerant Nash equilibria has been introduced as a way of studying the robustness of Nash equilibria. Under this notion, a fixed number of players are allowed to…
Sequential decomposition of stochastic Stackelberg games
Deepanshu Vasal
In this paper, we consider a discrete-time stochastic Stackelberg game with a single leader and multiple followers. Both the followers and the leader together have conditionally in…
Model-free Reinforcement Learning for Non-stationary Mean Field Games
Rajesh K Mishra, Deepanshu Vasal, Sriram Vishwanath
In this paper, we consider a finite horizon, non-stationary, mean field games (MFG) with a large population of homogeneous players, sequentially making strategic decisions, where e…
Decentralized multi-agent reinforcement learning with shared actions
Rajesh K Mishra, Deepanshu Vasal, Sriram Vishwanath
In this paper, we propose a novel model-free reinforcement learning algorithm to compute the optimal policies for a multi-agent system with cooperative agents where each agent…
Mechanism Design for Large Scale Network Utility Maximization
Meng Zhang, Deepanshu Vasal
Network utility maximization (NUM) is a general framework for designing distributed optimization algorithms for large-scale networks. An economic challenge arises in the presence o…
Sequential decomposition of discrete memoryless channel with noisy feedback
Deepanshu Vasal
In this paper, we consider a discrete memoryless point to point channel with noisy feedback, where there is a sender with a private message that she wants to communicate to a recei…
Master equation of discrete time graphon mean field games and teams
Deepanshu Vasal, Rajesh K Mishra, Sriram Vishwanath
In this paper, we present a sequential decomposition algorithm equivalent of Master equation to compute GMFE of GMFG and graphon optimal Markovian policies (GOMPs) of graphon mean…