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researcher

M. Gerstgrasser

7 papers hereh-index 7171 citations22 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author3

Across the 6 of 7 papers where every author was matched, so the position is known.

fields
  • cs.GT4
  • cs.LG2
  • stat.ML1

identity via Semantic Scholar / OpenAlex

activity
20172023
most citedSelectively Sharing Experiences Improves Multi-Agent Reinforcement Learning

4 citations · 9 across the 7 of their papers we have counts for

collaborators
Showing 2022Show all

2 papers · 1 filter

cs.GT2022

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…

cs.GT2022★ 1 cited

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.