Hedging under uncertainty: regret minimization meets exponentially fast convergence

DOI10.1007/978-3-319-66700-3_20zbMath1403.91023OpenAlexW2742389002WikidataQ60142053 ScholiaQ60142053MaRDI QIDQ681880

Amélie Héliou, Panayotis Mertikopoulos, Johanne Cohen

Publication date: 13 February 2018

Full work available at URL: https://doi.org/10.1007/978-3-319-66700-3_20

zbMATH Keywords

Nash equilibriumexponential weightsdominated strategiesno-regret learning

Mathematics Subject Classification ID

Noncooperative games (91A10) (n)-person games, (n>2) (91A06) Rationality and learning in game theory (91A26) Software, source code, etc. for problems pertaining to game theory, economics, and finance (91-04)

Related Items (4)

Continuous-Time Convergence Rates in Potential and Monotone Games ⋮ Opinion dynamics with limited information ⋮ Learning in games with continuous action sets and unknown payoff functions ⋮ Opinion dynamics with limited information

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