Deep Reinforcement Learning
Combines neural networks with a reinforcement learning architecture to enable software-defined agents to learn the best actions possible in virtual environment scenarios to maximize the notion of cumulative reward.
Areas of application
- Autonomous Vehicles
- Robotics
- Supply Chain Optimizations
- Scheduling Problems
- Advertisement Systems
- Retrieval Systems
- Financial Trading
- Healthcare
Example
AlphaGo, autonomous vehicles, and sophisticated recommendation systems are recent advancements in AI that have been made possible through deep reinforcement learning.