Prior deep learning experience (e.g. ELEC_ENG/COMP_ENG 395/495 Deep Learning Foundations from Scratch ) and strong familiarity with the Python programming language. Python will be used for all coding ...

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 ...

Microsoft is adding Python language support to its open source deep learning toolkit for developers. The kit, formerly known as Computational Network Toolkit (CNTK) and now called Microsoft ...

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, ...

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

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.

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

Reinforcement learning and simulation are essential to solving the constraints and novel challenges that take place in factories and supply chains.