Explainable Reinforcement Learning is a method where computer programs learn to make decisions, and it is explained why they make these decisions.
Imagine a robot learning how to catch a ball. Explainable Reinforcement Learning helps us understand why the robot makes a certain movement in a particular situation.
This way, people can better comprehend how and why a program acts, which is especially important when the decisions are important or complex.
These explanations help build trust in the technology and make it easier to identify problems.