Human social learning is increasingly occurring on online social platforms, such as Twitter, Facebook, and TikTok. On these platforms, algorithms exploit existing social-learning biases (i.e., towards ...

Online algorithms are central to solving resource allocation and matching challenges in dynamic environments where decisions must be made without complete knowledge of future events. Research in this ...

Supervised learning algorithms learn from labeled data, where the desired output is known. These algorithms aim to build a model that can predict the output for new, unseen input data. Let’s take a ...

In life, we sometimes have to make decisions without all the information we want; that’s true in computer science, too. This is the realm of online algorithms — which, despite their name, don’t ...

Researchers have introduced an online model-based reinforcement learning algorithm that trains robots directly from real-world interactions, bypassing extensive simulation. The approach builds a ...