Autonomous systems hold great promise in manufacturing and heavy industry. As technology has advanced, sensing technologies and automation systems have transformed what was once a highly manual sector into an…
Unlocking the potential of AI in manufacturing with machine teaching and deep reinforcement learning
Machine teaching and deep reinforcement learning offer new opportunities to manufacturers looking to optimize complex processes.
Deep Reinforcement Learning (DRL) techniques have allowed deep neural networks (DNN) based AI to move from theoretical concepts in the research lab to real-life, business solutions. Although tools such as the Microsoft Project Bonsai toolchain have tremendously streamlined, accelerated, and simplified the design, training, and deployment of Autonomous Systems AI agents, it does not mean they suddenly became simple…
Before diving deep into the concept of using simulators to solve Reinforcement Learning (RL) real-world problems, let’s understand the basics of RL. What is Reinforcement Learning? Reinforcement Learning (RL) is an…
In Deep Reinforcement Learning (DRL), an agent needs to interact with the environment (either physical or simulated) by performing actions to obtain rewards. The agent’s goal is to maximize its rewards and learns by adjusting its policy (the agent’s strategy) based on…
What is Reinforcement Learning? Deep Reinforcement Learning (DRL) or simply Reinforcement Learning (RL) is an area of machine learning that focuses on the training and decision-making abilities of AI agents.…