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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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0111 · Feb 202019922001200920172026
3 results for non-exploitability

LAFF algorithm balances adaptability and non-exploitability in repeated games.

problem Low regret in repeated games against unknown opponent classes.
method LAFF algorithm searches within sub-algorithms optimal for each opponent class and uses a punishment policy for exploitation.
result LAFF guarantees sublinear regret uniformly over possible opponents, except exploitative ones, for which it guarantees linear regret.

Paper tackles multiplayer symmetric games, securing equal share for n players.

problem Multiplayer games lack unique equilibria, making guarantees unreliable.
method Identifies conditions for equal share, designs efficient algorithms inspired by no-regret learning.
result Proves algorithms achieve approximate equal share across various settings.

Research tackles alliance formation in many-player zero-sum games, showing reinforcement learning fails but a contract mechanism can help.

problem Tackles the challenge of alliance formation in many-player zero-sum games.
method Demonstrates the social dilemma aspect of alliance formation, introduces a contract mechanism to augment reinforcement learning.
result Naïve reinforcement learning fails to form alliances, but a contract mechanism can help.