Reinforcement learning is one of the exciting branches of artificial intelligence. It plays an important role in game-playing AI systems, modern robots, chip-design systems, and other applications.

Imagine trying to teach a child how to solve a tricky math problem. You might start by showing them examples, guiding them step by step, and encouraging them to think critically about their approach.

The Allen Institute for AI (Ai2) recently released what it calls its most powerful family of models yet, Olmo 3. But the company kept iterating on the models, expanding its reinforcement learning (RL) ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I will identify and discuss an important AI ...

In June 2021, scientists at the AI lab DeepMind made a controversial claim. The researchers suggested that we could reach artificial general intelligence (AGI) using one single approach: reinforcement ...

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Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

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, ...

“We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT ...

Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...