Deep reinforcement learning is much more complicated than the other branches of machine learning. But in this post, I’ll try to demystify it without going into the technical details. States ...

Likewise, OpenAI trained deep reinforcement learning to beat the best human teams at Dota 2. Just like deep artificial neural networks began to find business applications in the mid-2010s, ...

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 ...

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 ...

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, ...

The technique proposed by the EA researchers overcomes these limits with “adversarial reinforcement learning,” a technique inspired by generative adversarial networks (GAN), a type of deep ...