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Episode 27: Noam Brown, FAIR, on achieving human-level performance in poker and Diplomacy, and the power of spending compute at inference time

Generally Intelligent

CHAPTER

Counterfactual Regret Minimization

Counterfactual regret minimization was developed in 2007. It's really an extension of regular regret minimization that's been around since the 50s. The basic idea is you have a regret value for each of your actions. And then any algorithm that minimizes regret, the average over all the iterations is proven to converge to an action.

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