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 ...
2). Additional architectures in the reviewed studies include an NLP-driven architecture with contextual bandit algorithm (Cai et al., 2021) and knowledge-based system accessing a vast domain-specific database to deliver accurate information (Chang et al., 2022b). Further, the chatbots we ...
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 ...
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...
It then uses features like machine learning and business intelligence to algorithmically refine it down to create highly personalized and contextualized offers that maximize conversion. As a business, we’ve already made big strides in this arena with our Beyond NDC and Retail Intelligence product ...
At the core of it all, our ultimate goal remains the same — to create a Wuxia game that feels like a playable Kung Fu movie. Every design decision we make serves to bring that vision to life. Screenshot: S-GAME I know pl...
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 ...