4 citations · 9 across the 7 of their papers we have counts for
7 papers
Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning
Matthias Gerstgrasser, Tom Danino, Sarah Keren
We present a novel multi-agent RL approach, Selective Multi-Agent Prioritized Experience Relay, in which agents share with other agents a limited number of transitions they observe…
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning
Matthias Gerstgrasser, David C. Parkes
Stackelberg equilibria arise naturally in a range of popular learning problems, such as in security games or indirect mechanism design, and have received increasing attention in th…
Stackelberg POMDP: Learning to Lead via Reinforcement Learning
Gianluca Brero, Alon Eden, Darshan Chakrabarti +6
Many real-world domains--including e-commerce platform design, security planning, and multi-agent coordination--feature leader-follower problems where one decision-maker commits to…
Collaboration Promotes Group Resilience in Multi-Agent RL
Ilai Shraga, Guy Azran, Matthias Gerstgrasser +3
To effectively operate in various dynamic scenarios, RL agents must be resilient to unexpected changes in their environment. Previous work on this form of resilience has focused on…
Reinforcement Learning of Sequential Price Mechanisms
Gianluca Brero, Alon Eden, Matthias Gerstgrasser +2
We introduce the use of reinforcement learning for indirect mechanisms, working with the existing class of sequential price mechanisms, which generalizes both serial dictatorship a…
Multi-unit Bilateral Trade
Matthias Gerstgrasser, Paul W. Goldberg, Bart de Keijzer +2
We characterise the set of dominant strategy incentive compatible (DSIC), strongly budget balanced (SBB), and ex-post individually rational (IR) mechanisms for the multi-unit bilat…
Riemannian tangent space mapping and elastic net regularization for cost-effective EEG markers of brain atrophy in Alzheimer's disease
Wolfgang Fruehwirt, Matthias Gerstgrasser, Pengfei Zhang +11
The diagnosis of Alzheimer's disease (AD) in routine clinical practice is most commonly based on subjective clinical interpretations. Quantitative electroencephalography (QEEG) mea…