82 citations · 166 across the 43 of their papers we have counts for
17 papers · 1 filter
Communication-efficient and Differentially-private Distributed Nash Equilibrium Seeking with Linear Convergence
Xiaomeng Chen, Wei Huo, Kemi Ding +2
The distributed computation of a Nash equilibrium (NE) for non-cooperative games is gaining increased attention recently. Due to the nature of distributed systems, privacy and comm…
Compression-based Privacy Preservation for Distributed Nash Equilibrium Seeking in Aggregative Games
Wei Huo, Xiaomeng Chen, Kemi Ding +2
This paper explores distributed aggregative games in multi-agent systems. Current methods for finding distributed Nash equilibrium require players to send original messages to thei…
Policy Gradient-based Model Free Optimal LQG Control with a Probabilistic Risk Constraint
Arunava Naha, Subhrakanti Dey
In this paper, we investigate a model-free optimal control design that minimizes an infinite horizon average expected quadratic cost of states and control actions subject to a prob…
An Efficient Distributed Nash Equilibrium Seeking with Compressed and Event-triggered Communication
Xiaomeng Chen, Wei Huo, Yuchi Wu +2
Distributed Nash equilibrium (NE) seeking problems for networked games have been widely investigated in recent years. Despite the increasing attention, communication expenditure is…
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization
Nicolò Dal Fabbro, Michele Rossi, Luca Schenato +1
Edge networks call for communication efficient (low overhead) and robust distributed optimization (DO) algorithms. These are, in fact, desirable qualities for DO frameworks, such a…
Deterministic policy gradient based optimal control with probabilistic constraints
Arunava Naha, Subhrakanti Dey
This paper studies a deep deterministic policy gradient (DDPG) based actor critic (AC) reinforcement learning (RL) technique to control a linear discrete-time system with a quadrat…