3 citations · 6 across the 5 of their papers we have counts for
7 papers
Welfare Measure for Resource Allocation with Algorithmic Implementation: Beyond Average and Max-Min
Ezra Tampubolon, Holger Boche
In this work, we propose an axiomatic approach for measuring the performance/welfare of a system consisting of concurrent agents in a resource-driven system. Our approach provides…
Coordinated Online Learning for Multi-Agent Systems with Coupled Constraints and Perturbed Utility Observations
Ezra Tampubolon, Holger Boche
Competitive non-cooperative online decision-making agents whose actions increase congestion of scarce resources constitute a model for widespread modern large-scale applications. T…
On Information Asymmetry in Competitive Multi-Agent Reinforcement Learning: Convergence and Optimality
Ezra Tampubolon, Haris Ceribasic, Holger Boche
In this work, we study the system of interacting non-cooperative two Q-learning agents, where one agent has the privilege of observing the other's actions. We show that this inform…
Resource-Aware Control via Dynamic Pricing for Congestion Game with Finite-Time Guarantees
Ezra Tampubolon, Haris Ceribasic, Holger Boche
Congestion game is a widely used model for modern networked applications. A central issue in such applications is that the selfish behavior of the participants may result in resour…
Pricing Mechanism for Resource Sustainability in Competitive Online Learning Multi-Agent Systems
Ezra Tampubolon, Holger Boche
In this paper, we consider the problem of resource congestion control for competing online learning agents. On the basis of non-cooperative game as the model for the interaction be…
Robust Online Learning for Resource Allocation -- Beyond Euclidean Projection and Dynamic Fit
Ezra Tampubolon, Holger Boche
Online-learning literature has focused on designing algorithms that ensure sub-linear growth of the cumulative long-term constraint violations. The drawback of this guarantee is th…