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aamas-experiments

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Use when designing or auditing AAMAS experiments - self-play and population-based training, opponent selection, equilibrium and regret metrics, game-theoretic simulations, ablations, seeds, hyperparameters, compute, and claim-to-evidence fit - with emphasis on experiments that probe the interaction rather than chase a single-agent leaderboard.

When to use

• designing AAMAS experiments
• auditing AAMAS experiments
• self-play and population-based training
• opponent selection
• equilibrium and regret metrics
• game-theoretic simulations
• ablations
• claim-to-evidence fit

When not to use

• chasing a single-agent leaderboard

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