On the Bandit Tour, I was given very little direction. I was simply asked to capture it and make sense of it. But I did know we’d be traveling, so I’d need to capture stable footage of our vehicles on the road for B-roll. (That’s filler footage, more on that later.) I al...
Whereas existing research on CDM primarily focuses on making binary decisions, we focus here on CDM applied to solving contextual multi-armed bandit (CMAB) problems, where the goal is to exploit contextual information to select the best arm among a set. To address the limiting assumptions of ...
An alternative solution is to use a “contextual bandit,” an upgraded version of the multi-armed bandit that takes contextual information into account. Instead of creating a separate MAB for each combination of characteristics, the contextual bandit uses “function approximation,” which tries to mo...
separated by a few seconds rest period. The first was a quiz task used as a mood induction procedure35,36, the second was a choice task used to unravel the effects of mood induction on decision-making (Fig.1). In the quiz task, participants had to answer general knowledge questions and ...
We aim to design a model which helps us understand the relationship between risk and benefit and their moderating factors on final information disclosure in the group. To create realistic scenarios of group decision making where users can control the amount of information disclosed, we developed ...
Without going too much into the details (that could be the subject of another post), our contextual bandit uses supervised machine learning to predict the performance of each ad based on location, device type, gender, age, etc. The benefit of the contextual bandit is that it uses one machin...