Search Results for author: Ryann Sim

Found 4 papers, 0 papers with code

Optimal No-Regret Learning in General Games: Bounded Regret with Unbounded Step-Sizes via Clairvoyant MWU

no code implementations29 Nov 2021 Georgios Piliouras, Ryann Sim, Stratis Skoulakis

We shift away from this paradigm by defining a novel algorithm that we call Clairvoyant Multiplicative Weights Updates (CMWU).

Online Learning in Periodic Zero-Sum Games

no code implementations NeurIPS 2021 Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian Ratliff

Classical learning results build on this theorem to show that online no-regret dynamics converge to an equilibrium in a time-average sense in zero-sum games.

Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games

no code implementations15 Dec 2020 Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian Ratliff

The predominant paradigm in evolutionary game theory and more generally online learning in games is based on a clear distinction between a population of dynamic agents that interact given a fixed, static game.

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