activity
20192022
most citedGradient-Tracking over Directed Graphs for solving Leaderless Multi-Cluster Games

6 citations · 8 across the 5 of their papers we have counts for

collaborators

6 papers

eess.SY20222 cited

Projected gradient-tracking in multi-cluster games and its application to power management

Jan Zimmermann, Tatiana Tatarenko, Volker Willert +1

We are concerned with a distributed approach to solve multi-cluster games arising in multi-agent systems. In such games, agents are separated into distinct clusters. The agents bel…

cs.GT2021

Gradient Play in -Cluster Games with Zero-Order Information

Tatiana Tatarenko, Jan Zimmermann, Jürgen Adamy

We study a distributed approach for seeking a Nash equilibrium in -cluster games with strictly monotone mappings. Each player within each cluster has access to the current value…

eess.SY20216 cited

Gradient-Tracking over Directed Graphs for solving Leaderless Multi-Cluster Games

Jan Zimmermann, Tatiana Tatarenko, Volker Willert +1

We are concerned with finding Nash Equilibria in agent-based multi-cluster games, where agents are separated into distinct clusters. While the agents inside each cluster collaborat…

eess.SY2020

Revisiting Consensus-Based Energy-Management in Smart Grid with Transmission Losses and Directed Communication

Jan Zimmermann, Tatiana Tatarenko, Volker Willert +1

We discovered a deficiency in Algorithm 1 and Theorem 3 of [1]. The algorithm called CEMA aims to solve an energy management problem distributively. However, by means of a counter…

eess.SY2020

Projected Push-Sum Gradient Descent-Ascent for Convex Optimizationwith Application to Economic Dispatch Problems

Jan Zimmermann, Tatiana Tatarenko, Volker Willert +1

We propose a novel algorithm for solving convex, constrained and distributed optimization problems defined on multi-agent-networks, where each agent has exclusive access to a part…

eess.SP2019

Penalized Push-Sum Algorithm for Constrained Distributed Optimization with Application to Energy Management in Smart Grid

Tatiana Tatarenko, Jan Zimmermann, Volker Willert andJürgen Adamy

We study distributed convex constrained optimization on a time-varying multi-agent network. Each agent has access to its own local cost function, its local constraints, and its ins…