Shortest path variants solve problems where basic algorithms need modification. You'll face constraints like limited resources, multiple starting points, or unusual edge weights.
The core insight is state expansion. Instead of tracking just your position, you track position plus additional information.
This simplifies problem into a standard shortest path on a larger state space. When you understand this pattern, these problems won't be hard anymore.
I'll show you exactly how this works in the problems in this section.
