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A survey on algorithms for Nash equilibria in finite normal-form games
This paper reviews various algorithms computing the Nash equilibrium and its approximation solutions in finite normal-form games from both theoretical and empirical perspectives.
No-regret Learning in Repeated First-Price Auctions with Budget Constraints
Recently the online advertising market has exhibited a gradual shift from second-price auctions to first-price auctions.
Is Nash Equilibrium Approximator Learnable?
In this paper, we investigate the learnability of the function approximator that approximates Nash equilibrium (NE) for games generated from a distribution.
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment
In addition, we use a novel agent network named Population Invariant agent with Transformer (PIT) to realize the coordination transfer in more varieties of scenarios.
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