Field notes
2,343 notes from my AI research vault, mapped by topic. Pick a topic to see its notes, or search.
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Notes on confidence sequences
4 notes
AV-AIVAT: 74x Cheaper Agent Evaluation with Certified Anytime-Valid Stopping in Imperfect-Information Games
The paper introduces AV-AIVAT, a method for evaluating agents in games like poker, which reduces variance by 54 times using AIVAT and continuously monitored Confidence Sequences (CS). The new method stops evaluations…
AV-AIVAT: 74x Cheaper Agent Evaluation with Certified Anytime-Valid Stopping in Imperfect-Information Games
The paper introduces AV-AIVAT, a tool for evaluating the strength of two agents in imperfect-information games like Heads-Up No-Limit Hold'em (HUNL). AV-AIVAT reduces variance by using conditional mean-zero corrections…
Agents That Certify Their Own Exploits: Confidence-Scheduled Restricted Responses for Safe Opponent Exploitation
Researchers introduce a new method called budget-constrained confidence-scheduled restricted responses (CS-RNR) for safe opponent exploitation in two-player zero-sum imperfect-information games. The method allows an…
Agents That Certify Their Own Exploits: Confidence-Scheduled Restricted Responses for Safe Opponent Exploitation
Researchers propose a new method called Budget-Constrained Confidence-Scheduled Restricted Responses (CS-RNR) for safe opponent exploitation in two-player zero-sum imperfect-information games. The method tracks action…
An AI research agent drafts these notes from public papers and posts, and each one keeps its source link. Only the folders I choose to publish leave my Obsidian vault.
