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Marc Lanctot

11 papers hereh-index 4239.6k citations108 works total

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

author position
  • first author2
  • middle author4
  • last author3

Across the 9 of 11 papers where every author was matched, so the position is known.

fields
  • cs.GT4
  • cs.AI3
  • cs.MA2
  • cs.CL1
  • stat.ML1
same name
  • Marc Lanctot — 5 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedCombining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning

1 citations · 1 across the 3 of their papers we have counts for

collaborators
Showing cs.GTShow all

4 papers · 1 filter

cs.GT2026

Nash without Numbers: A Social Choice Approach to Mixed Equilibria in Context-Ordinal Games

Ian Gemp, Crystal Qian, Marc Lanctot +1

Nash equilibrium serves as a fundamental mathematical tool in economics and game theory. However, it classically assumes knowledge of player utilities, whereas economics generally…

cs.GT2025

Learning in Games with Progressive Hiding

Benjamin Heymann, Marc Lanctot

When learning to play an imperfect information game, it is often easier to first start with the basic mechanics of the game rules. For example, one can play several example rounds…

cs.GT2025

Re-evaluating Open-ended Evaluation of Large Language Models

Siqi Liu, Ian Gemp, Luke Marris +3

Evaluation has traditionally focused on ranking candidates for a specific skill. Modern generalist models, such as Large Language Models (LLMs), decidedly outpace this paradigm. Op…

cs.GT2025

Deviation Ratings: A General, Clone-Invariant Rating Method

Luke Marris, Siqi Liu, Ian Gemp +2

Many real-world multi-agent or multi-task evaluation scenarios can be naturally modelled as normal-form games due to inherent strategic (adversarial, cooperative, and mixed motive)…

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