AI Response Comparator

**Recursion** is a fundamental concept in programming where a function calls itself in order to solve a problem. The idea is to break a complex problem into smaller instances of the same problem until you reach a trivial case that can be solved directly.

### Key Components:
1. **Base Case**: The condition that stops the recursion
2. **Recursive Case**: The part where the function calls itself with modified arguments

### Simple Example: Fibonacci Numbers

```python
def fibonacci(n):
    if n <= 0:
        return 0
    elif n == 1:
        return 1
    else:
        return fibonacci(n-1) + fibonacci(n-2)
```

This function calculates the nth Fibonacci number by summing the two preceding numbers, recursing until it hits the base cases of 0 or 1.

### When to Use Recursion Over Iteration:

Recursion shines in scenarios where:
- **Tree/graph traversal**: Navigating hierarchical data structures
- **Divide and conquer**: Problems like merge sort or binary search
- **Mathematical definitions**: Problems naturally defined recursively (factorials, Fibonacci)
- **Backtracking problems**: Sudoku solvers, maze navigation, permutation generation

### Caveats:
- Recursion uses more memory (call stack overhead)
- Risk of stack overflow for deep recursion
- Some languages optimize tail recursion, but many do not

In practice, many recursive solutions can be converted to iterative ones using an explicit stack, but the recursive version is often more elegant and easier to reason about.