Imagine a robot trying to catch a ball for the first time. It misses, but then it tries again, and again, until it gets better at catching. That’s learning! Just like how you learn to ride a bike by falling down a few times, robots use trial and error to get smarter over time. They keep track of what worked and what didn’t, and they adjust their actions based on that. It might seem simple, but it's the start of something big!
Examples
- A robot learns to catch a ball by dropping it over and over until it gets better at timing.
- A toy robot learns to move forward by bumping into walls and figuring out when to turn.
- A robot learns to sort blocks by trying different ways of picking them up and seeing which works best.
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See also
- How Does a Robot Actually Learn New Tasks?
- How Does a Computer Learn?
- How Does a Robot Learn to Walk?
- What Is the Difference Between ‘Artificial Intelligence’ and ‘Machine Learning’?
- How Does a Computer Know What You're Thinking?
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