Enterprises embedding agentic AI into workflows are facing unexpected infrastructure cost surges due to continuous, self-initiated system activity. Experts warn that without governance frameworks like ...

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Deep Reinforcement Learning (DRL) is a subfield of machine learning that combines neural networks with reinforcement learning techniques to make decisions in complex environments. It has been applied ...

This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, ...

Artificial intelligence is rapidly transforming the game of bridge, from cutting-edge bidding algorithms that rival champions to accessible training tools for players of all levels. Researchers are ...

Schematic diagram of the NOEO-based photonic accelerator. (a) Experimental setup of the NOEO. (b) Evolution of the temporal sequences generated by the NOEO with an increasing net gain β. (c) MAB ...

Picture this: a self-driving car smoothly navigating treacherous mountain roads with consecutive hairpin turns – a scenario that would challenge even the most experienced human drivers. This vision is ...

AI developers are getting more creative in how they acquire data to train AI models. For instance, they’re paying startups to develop copies of popular apps, like Salesforce or Excel, to teach models ...

Have you ever wished AI could truly understand the complexities of your field—not just replicate data but reason through intricate, domain-specific challenges? Whether you’re a researcher analyzing ...