We consider the problem of fitting a reinforcement learning (RL) model to some given behavioral data under a multi-armed bandit environment. These models have received much attention in recent years ...

Abstract: Contextual multi-armed bandit algorithms serve as an effective technique to address online sequential decision-making problems. Despite their popularity, when it comes to off-the-shelf tools ...

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Gender-based violence and discrimination are persistent across societies, and rates across Palestine were already unacceptable before the current crisis. The toll of armed conflict is felt heavily ...

上下文强盗的与众不同之处在于，决策过程是根据上下文进行的。在这种情况下，上下文指的是一组可以影响操作结果的可观察变量。这一添加使得强盗问题更接近现实世界的应用，例如个性化推荐、临床试验或广告投放，其中的决定取决于具体情况。 上下文 ...

The multi-armed bandit (MAB) problem models a decision-maker that optimizes its actions based on current and acquired new knowledge to maximize its reward. This type of online decision is prominent in ...