For repeated games against an unknown optimizer type, the paper gives polynomial-time optimal no-regret commitment, near-optimal general commitment when the game or support size is constant, a polynomial-per-step maximin algorithm, and an NP-hardness result.
Auctions between regret-m inimizing agents
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Learning to Play Against Unknown Opponents
For repeated games against an unknown optimizer type, the paper gives polynomial-time optimal no-regret commitment, near-optimal general commitment when the game or support size is constant, a polynomial-per-step maximin algorithm, and an NP-hardness result.