Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

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 ...

Deep reinforcement learning is one of the most interesting branches ofartificial intelligence. It is behind some of the most remarkable achievements of the AI community, including beating human ...

You might have seen headlines sounding the alarm about the safety of an emerging technology called agentic AI.

In their decades-long chase to create artificial intelligence, computer scientists have designed and developed all kinds of complicated mechanisms and technologies to replicate vision, language, ...

Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...

This article is published by AllBusiness.com, a partner of TIME. What is "Reinforcement Learning"? Reinforcement Learning (RL) is a type of machine learning where a model learns to make decisions by ...

Researchers at the Japan Advanced Institute of Science and Technology (JAIST) implemented a framework named PenGym that supports the creation of realistic training environments for reinforcement ...

VentureBeat presents: AI Unleashed - An exclusive executive event for enterprise data leaders. Network and learn with industry peers. Learn More DeepMind this week released Acme, a framework intended ...

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...