Humans adapt by learning from others, but risk acquiring maladaptive behaviors when learning from individuals facing different conditions. We present an evolutionary model exploring how individuals ...

This site displays a prototype of a “Web 2.0” version of the daily Federal Register. It is not an official legal edition of the Federal Register, and does not replace the official print version or the ...

In a paper posted last week by Google's DeepMind unit, researchers Chengrun Yang and team created a program called OPRO that makes large language models try different prompts until they reach one that ...

Abstract: By utilizing a neural-network-based adaptive critic mechanism, the optimal tracking control problem is investigated for nonlinear continuous-time (CT) multiplayer zero-sum games (ZSGs) with ...

Deep learning networks have been trained to recognize speech, caption photographs, and translate text between languages at high levels of performance. Although applications of deep learning networks ...

The Locally Competitive Algorithm (LCA) is a biologically plausible computational architecture for sparse coding, where a signal is represented as a linear combination of elements from an ...

Quantum computing and artificial intelligence, combined together, may revolutionize future technologies. A significant school of thought regarding artificial intelligence is based on generative models ...

What is the effect of programming languages on software quality? This question has been a topic of much debate for a very long time. In this study, we gather a very large data set from GitHub (728 ...

What separates statistics from machine learning? That's a broad topic which has been treated many times. Much of what has been written on this topic is good, much is bad. But I find that the stats vs.