Reinforcement Learning: What’s a “Reward” Really About?

A super simple way to understand rewards in AI, with fun examples!

Photo by Igor Omilaev on Unsplash

Okay, picture this: You’re teaching your little sibling to ride a bike. Every time they pedal without toppling over, you shout, “Woohoo!” or promise them a chocolate bar later. That shout or chocolate? That’s how you tell them, “Hey, you’re doing great! Keep it up!”

That’s pretty much how Reinforcement Learning (RL) works, too. Let’s dive in — don’t worry, it’s easier than it sounds!

What’s Reinforcement Learning, Anyway?

Reinforcement Learning is a way computers learn stuff by trying things out. There’s no teacher saying, “Do this, don’t do that.” Instead, the computer (or “agent”) just experiments, checks what happens, and figures out what’s working based on rewards.

What’s a “Reward” in RL?

In RL, a reward is like the computer’s way of knowing if it did something right or wrong. It’s a number (fancy, right?) that says:

• You nailed it! (Positive reward)
• Oops, bad move. (Negative reward)

But let’s make it more fun:

• Rewards are like gold stars — yay, keep going!
• Or they’re like a buzzer —…