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.

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 ...

Their new project includes a 3D environment with realistic dynamics and deep reinforcement learning agents that can learn to solve a wide range of challenges.

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

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 ...

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, ...

Amazon is making it clear that it believes that reinforcement learning (RL) should be a first-class participant in the ML portfolio considered by enterprises. Amazon has applied RL and other ML ...

The "reward-is-enough" hypothesis suggests that reinforcement learning alone could lead to AGI.