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…