AI algorithms for deep-reinforcement learning have demonstrated the ability to learn at very high levels in constrained domains.

Deep reinforcement learning has helped solve very complicated challenges and will continue to be an important interest for the AI community.

Both deep learning and reinforcement learning are machine learning functions, which in turn are part of a wider set of artificial intelligence tools. What makes deep learning and reinforcement ...

Rather than generating potential outcomes based on historical data, deep reinforcement learning teaches AI agents and machines with the time-tested "carrot and stick" method.

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 ...

ELEC_ENG 373, 473: Deep Reinforcement Learning from Scratch VIEW ALL COURSE TIMES AND SESSIONS Prerequisites Prior deep learning experience (e.g. ELEC_ENG/COMP_ENG 395/495 Deep Learning Foundations ...

A new technique from Stanford researchers creates AI virtual agents that can evolve both in their physical structure and learning capacities.

The application of Deep Reinforcement Learning (DRL) in economics has been an area of active research in recent years. A number of recent works have shown how deep reinforcement learning can be used ...