Practical reinforcement learning

Now that you have an intuitive understanding of what AI really means and the various classes of algorithm that drive its development, we will now focus on the practical aspects of building a reinforcement learning machine.

Here are the core concepts that you need to be aware of to develop reinforcement learning systems:

• Agent
• Rewards
• Environment
• State
• Value function
• Policy

Agent

In the reinforcement learning world, a machine is run or instructed by a (software) agent. The agent is the part of the machine that possesses intelligence and makes decisions on what to do next. You will come across the term "agent" several times as we dive deeper into reinforcement learning. Reinforcement...