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M. Ueda

21 papers hereh-index 9226 citations53 works total

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

author position
  • sole author13
  • first author7
  • last author1

Across the 21 of 21 papers where every author was matched, so the position is known.

fields
  • cond-mat.stat-mech6
  • cs.GT5
  • physics.soc-ph4
  • cond-mat.dis-nn2
  • q-bio.PE2
  • math.CO1
same name
  • M. Ueda — 13 papers, h 6
  • M. Ueda — 11 papers, h 5
  • M. Ueda — 8 papers, h 10
  • M. Ueda — 3 papers, h 4
  • M. Ueda — 2 papers, h 32
  • M. Ueda — 2 papers, h 7

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
20132023
most citedEffect of information asymmetry in Cournot duopoly game with bounded rationality

41 citations · 204 across the 21 of their papers we have counts for

collaborators
Showing physics.soc-phShow all

4 papers · 1 filter

physics.soc-ph2022★ 2 cited

Unexploitable games and unbeatable strategies

Masahiko Ueda

Imitation is simple behavior which uses successful actions of others in order to deal with one's own problems. Because success of imitation generally depends on whether profit of a…

physics.soc-ph2022★ 8 cited

Necessary and Sufficient Condition for the Existence of Zero-Determinant Strategies in Repeated Games

Masahiko Ueda

Zero-determinant strategies are a class of memory-one strategies in repeated games which unilaterally enforce linear relationships between payoffs. It has long been unclear for wha…

physics.soc-ph2021★ 8 cited

Unbeatable Tit-for-Tat as a Zero-Determinant Strategy

Masahiko Ueda

Tit-for-Tat strategy is a strategy in repeated two-player symmetric games which imitates the previous action of the opponent. We show that the Tit-for-Tat strategy is a zero-determ…

physics.soc-ph2021★ 7 cited

Memory-two strategies forming symmetric mutual reinforcement learning equilibrium in repeated prisoners' dilemma game

Masahiko Ueda

We investigate symmetric equilibria of mutual reinforcement learning when both players alternately learn the optimal memory-two strategies against the opponent in the repeated pris…

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