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Learning how to choose the best and shortest path to solve a problem efficiently.
Imagine you are a robot delivery driver with only a tiny bit of battery left. If you take 10 steps to deliver a pizza when you could have taken 5, your battery might die! How do we find the 'secret shortcut' every single time?
When we give a robot instructions, we call that an algorithm. Sometimes, there are many different ways to finish the same task. For example, you could get to the school bus by walking around the whole block, or by walking straight out your front door. Efficiency is a big word that means doing a job in the best way possible without wasting time or energy. In computer science, the 'best' way is usually the one with the fewest steps. If a robot uses fewer steps, it saves battery and finishes its job faster!
Quick Check
If Robot A takes steps to pick up a ball and Robot B takes steps to pick up the same ball, which robot is more efficient?
Answer
Robot B is more efficient because it uses fewer steps.
To find the most efficient path, we have to become 'Step Detectives.' We look at two different sets of instructions and count how many actions are in each one. We use the rule of , where is the number of steps in the first path and is the number of steps in the second. If path has a smaller number, it is the winner! We always want the shortest path to save the robot's resources.
Robot Blue needs to get to the fridge.
1. Path 1: Move Forward, Move Forward, Turn Right, Move Forward. (Total steps = ) 2. Path 2: Move Forward, Turn Right, Move Forward, Turn Left, Move Forward, Turn Right. (Total steps = )
Since , Path 1 is the most efficient choice.
Quick Check
Why do computer scientists care about the number of steps in a program?
Answer
Because fewer steps make the program run faster and use less power.
Sometimes instructions have unnecessary steps. This happens when a robot does something and then immediately undoes it. Imagine if I told you: 'Take one step forward, then take one step backward, then take one step forward.' You ended up in the same place as if you had just taken one step forward! By removing these 'extra' steps, we make our algorithm lean and fast. This is called optimization.
Look at these instructions for a robot to move spaces to the right:
1. Move Right 2. Move Left 3. Move Right 4. Move Right
Step 1 and Step 2 cancel each other out! To simplify this, we remove them. The new efficient instructions are: 1. Move Right 2. Move Right
We went from steps down to steps!
A robot is in a maze. It has two choices to reach the exit:
Option A: Go through the 'Spinning Door' which requires: Move Forward (), Spin (), Move Forward (), Spin (), Move Forward (). Total = steps.
Option B: Go through the 'Long Hallway' which requires: Move Forward (). Total = steps.
Even though the hallway looks 'long,' it only takes steps compared to the steps in the spinning door path. Option B is more efficient!
What does 'Efficiency' mean in computer science?
If Path A has steps and Path B has steps, which one is more efficient?
Removing a 'Turn Left' followed by a 'Turn Right' can make an algorithm more efficient.
Review Tomorrow
Tomorrow morning, try to count how many steps it takes to get from your bed to the bathroom. Can you find a way to do it in 2 fewer steps?
Practice Activity
Draw a simple grid on paper. Place a 'Start' and an 'End' point. Draw two different paths and count the squares to see which one is the winner!