
25 - Cooperative AI with Caspar Oesterheld
AXRP - the AI X-risk Research Podcast
The Multi-Armed Bandit Problem and Regret Minimization
The chapter explores the multi-armed bandit problem, where the goal is to maximize reward by choosing between multiple options. It discusses scenarios with unknown reward distributions and the need for randomization. Additionally, it highlights the concept of regret minimization and its limitations in certain decision-making scenarios.
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