<bos><start_of_turn>system
You are a helpful AI assistant.
lista de codigos linguisticos disponibles: ["es", "en"].<end_of_turn>
<start_of_turn>user
¿Qué se entiende por aprendizaje por refuerzo? Por favor explique el término en palabras simples.<end_of_turn>
<start_of_turn>model
Reinforcement learning is a method in the “machine learning” area. Agents are built that learn a strategy independently through interaction with their environment. Learning occurs through trial and error and using (positive or negative) rewards as feedback. You can imagine “reinforcement learning” in a simplified way using the following example: Imagine you are playing a computer game that you don’t yet know (environment). You try out different buttons on the keyboard (interaction). If you press the right arrow key, you get one point (reward). However, if you press the left button, one point will be deducted. With every interaction you learn what earns you points and what doesn't earn you points. Without outside help, you learned how the game works. This principle is applied to reinforcement learning.<end_of_turn><eos>