The rapid rise of electric vehicles combined with breakthroughs in autonomous driving technology is reshaping the future of ...

A new study reveals that the next generation of blockchain defenses will not rely on fixed rules alone but on adaptive, learning-based systems capable of evolving alongside intelligent adversaries.

No body, no dopamine, no problem. Scientists have successfully coached lab-grown brain tissue to solve a classic robotics challenge, proving that the will to learn is hardwired into our neurons.

Every year, NeurIPS produces hundreds of impressive papers, and a handful that subtly reset how practitioners think about scaling, evaluation and system design. In 2025, the most consequential works ...

What happens when the strategies that propelled an entire field to unprecedented heights begin to falter? For artificial intelligence, this is no longer a hypothetical question. After years of ...

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms as well as supporting myriad research applications. Of particular interest ...

Accurately estimating the Q-function is a central challenge in offline reinforcement learning. However, existing approaches often rely on a single global Q-function, which struggles to capture the ...

Abstract: This study investigates the design of reward functions for deep reinforcement learning-based source term estimation (STE). Estimating the properties of unknown hazardous gas leakage using a ...

The authors present a biologically plausible framework for action selection and learning in the striatum that is a fundamental advance in our understanding of possible neural implementations of ...