how many successors are generated in backtracking search?

For standard backtracking search in AI (as asked in common MCQ-style questions), only 1 successor is generated at a time for each node.

Quick Scoop: Core Idea

Backtracking search behaves like depth-first search but is carefully implemented so that:

• It keeps track of which successor to try next for the current (partially expanded) node.
• It does not generate all children at once ; instead, it generates one successor, explores it fully , then comes back and generates the next one if needed.
• Because of this, at any given expansion step, the algorithm generates only 1 successor.

So, for the classic question:

“How many successors are generated in backtracking search?”

The accepted answer is:

• 1 successor per expansion step.

Why only 1 successor?

In backtracking:

1. You are usually building a partial solution (like assigning values to variables one by one).
2. At each step, you:
   • Pick the next variable or choice.
   • Generate one possible value/option (one successor).
   • Recurse (go deeper) with that choice.
3. If it fails later, you backtrack and:
   • Return to the previous node.
   • Generate the next single successor from there.

Because each node “remembers” which successor comes next, the algorithm never needs to store or expand all children simultaneously. This is why backtracking is memory efficient : it behaves like DFS with linear space in the depth of the tree.

Related exam-style fact

In many AI/CS MCQ sets, the explanation is:

• Each partially expanded node remembers which successor to generate next.
• Therefore, backtracking search generates 1 successor at a time , which reduces memory usage compared to algorithms that generate all successors at once.

TL;DR

• Answer: 1 successor at a time.
• Reason: Backtracking generates and explores each child sequentially rather than all at once, storing only what’s needed to know the next successor.