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.

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, ...

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 ...

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.